Welfare Footprint Framework: Methodological Foundations and Quantitative Assessment Guidelines

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This document provides foundational methodological guidelines and quantitative assessment standards for implementing the Welfare Footprint Framework (WFF). The guidelines outlined herein serve as a practical reference for conducting systematic, evidence-based measurement of animal welfare impacts, facilitating decision-making and benchmarking across sectors. This core documentation should be cited as: Alonso, W. J., & Schuck-Paim, C. (2025). Welfare Footprint Framework: Methodological Foundations and Quantitative Assessment Guidelines. Center for Welfare Metrics (Sao Paulo). https://doi.org/10.17605/osf.io/94bxs 1 Summary................................................................................................................................. 3 Innovative Tools and Metrics....................................................................................................4 Introduction............................................................................................................................. 5 Trademark Usage and Requirements........................................................................................ 6 Core Framework Components.................................................................................................. 6 Intraspecific Analyses............................................................................................................ 12 Definition of Analytical Boundaries........................................................................................ 12 I. Zootechnical Description..........................................................................................................13 II. Veterinary

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I. Zootechnical Description..........................................................................................................13 II. Veterinary Inventory................................................................................................................. 15 Biological Outcomes........................................................................................................ 16 Affective Experiences............................................................................................................17 Association Between Circumstances, Biological Outcomes, and Affective Experiences.20 III. Affective Quantification.......................................................................................................... 20 (A) Temporal Description Using Notation Systems.............................................................21 (B) Calculation of Cumulative Affect....................................................................................27 IV. Epidemiological Investigation................................................................................................ 29 V. Econometric Calculation......................................................................................................... 29 Cumulative Pain and Pleasure for Each Life-Fate................................................................30 Cumulative Pain and Pleasure for the Average Individual in a System.............................. 30 Welfare Footprint: Cumulative Pain and Pleasure per Unit of Product.............................. 30 Interspecific Scaling...............................................................................................................31 Welfare Footprint Expression and

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ling...............................................................................................................31 Welfare Footprint Expression and Notation.............................................................................32 Fundamental Requirements........................................................................................................ 32 Transparency Requirements..................................................................................................35 Expression Flexibility................................................................................................................... 36 Summary of Methodological Strengths.................................................................................. 37 References.............................................................................................................................39 2 Summary The Welfare Footprint Framework (WFF) is a scientifically rigorous methodology for assessing and quantifying animal welfare across different environments and living conditions, including food production systems and settings where animals are used for work, entertainment, research or companionship. It is unique in providing a comprehensive, comparable and biologically meaningful measure of welfare that connects directly to animal experience: time spent in affective states—both positive (Pleasure) and negative (Pain)—of varying intensities. By measuring the duration and intensity of lived affective experiences, the WFF enables meaningful comparisons of welfare impacts across species, environments, and production conditions. This time-based approach allows stakeholders to measure trade-offs between different welfare challenges or interventions, enabling the identification of

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is time-based approach allows stakeholders to measure trade-offs between different welfare challenges or interventions, enabling the identification of those changes providing the greatest welfare benefits relative to their costs. Although the subjective assessment of indirect evidence is inherent to all animal welfare assessments, in the WFF subjectivity is constrained in several ways, through a process that ensures explicit and documented disclosure of evidence-to-judgment pathways. To this end, the framework documents evidence from multiple disciplines—including behavioral, physiological, neurological, evolutionary, and pharmacological research— which are used to estimate how long animals spend in different Pain categories (Annoying, Hurtful, Disabling, or Excruciating) or Pleasure categories (Satisfaction, Joy, Euphoria, Bliss) as a result of each affective experience. A key strength of the WFF is its transparency: it makes all evidence and assumptions explicit, highlights knowledge gaps, and enables sensitivity analysis. The framework has been successfully applied to assess welfare impacts in diverse contexts, such as comparing the welfare impacts of different housing systems for laying hens [1] and the use of slower-growing breeds of broiler chickens [2]. While many of the WFF tools—such as the Pain-Track and Cumulative Pain metrics—also hold significant value for describing and quantifying human health and welfare, this document focuses specifically on their application to animal welfare, providing producers, policymakers, and consumers with a powerful, evidence-based decision-making tool. Additionally, this document serves as the foundation for the trademark registration process for the term "Welfare Footprint™". The registration of "Welfare

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ionally, this document serves as the foundation for the trademark registration process for the term "Welfare Footprint™". The registration of "Welfare Footprint™" as a trademark is intended to ensure that anyone employing the term must adhere to the established scientific methodology established by the WFF and transparency standards, thereby maintaining its integrity and comparability across different contexts and preventing misrepresentation of welfare impacts. 3 Innovative Tools and Metrics Pain-Track and Pleasure-Track Notation Systems ●​ Visual frameworks for describing negative (Pain-Track; [3,4]) and positive (Pleasure-Track; [5]) affective states over time. These systems allow for a structured representation of the intensity and duration of affective experiences. Cumulative Pain and Cumulative Pleasure Metrics ●​ Quantitative measures that integrate the total time animals spend in different affective intensities as a result of one or more affective experiences, over a target time period. These metrics allow for a comprehensive evaluation of welfare, making it possible to compare welfare across conditions, practices, systems and species [3–5]. Hierarchical Framework for the Description of Living Circumstances ●​ A structured model that categorizes the Life-Fates, Life Phases, and Circumstances that animals experience, which will give rise to several biological outcomes and affective experiences. This ensures a comprehensive welfare assessment, capturing all critical conditions animals are exposed to over their lives. Welfare Footprint Calculation ●​ A standardized methodology that integrates data from various analytical components—zootechnical, veterinary, epidemiological, and economic—to estimate Cumulative Pain and Pleasure per unit of

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s data from various analytical components—zootechnical, veterinary, epidemiological, and economic—to estimate Cumulative Pain and Pleasure per unit of product. This allows for direct welfare comparisons between animal-sourced products and systems. 4 Introduction The WFF provides a scientifically robust and evidence-based approach to assess and quantify the impacts of various living conditions and practices on animal welfare. It is applicable in all contexts where animals are involved, such as the development, production, and use of products and services. The WFF achieves this by measuring the cumulative time animals spend in different affective states—both negative and positive—and at varying levels of intensity. Within this framework, "Pain" and "Pleasure" serve as operational terms to represent negative and positive affective experiences, respectively. To distinguish technical definitions within the framework from their vernacular use, capitalization is applied to specific terms, including Pain, Pleasure, their respective intensity categories, and other key concepts. At the core of this framework are several novel concepts and tools designed to make welfare assessment both scientifically rigorous and practical. Key elements include the concept of Life-Fates, the Pain-Track and Pleasure-Track notation tools, the Cumulative Pain and Cumulative Pleasure metrics and the Welfare Footprint concept itself. Together these components create a complete picture of animal welfare impacts for any scenario of choice over any timeframe and for any species. Since its development, the WFF has demonstrated its utility across various applications, informing the design of interventions to improve animal welfare in contexts including the welfare of egg-laying hens, broiler

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ss various applications, informing the design of interventions to improve animal welfare in contexts including the welfare of egg-laying hens, broiler chickens and fish. It is designed to serve multiple audiences: ●​ Researchers: can quantify and compare animal welfare across species, production systems, living conditions, practices and contexts. ●​ Students: can learn a welfare assessment framework with direct applications in practice and policy. ●​ Veterinarians and animal care-takers: can describe, estimate, and compare Pain from diseases, injuries and physiological imbalances, leading to more effective Pain management and treatment. ●​ Industries: can identify, compare and mitigate the welfare impact of different practices in the production chain and estimate the cost-effectiveness of different interventions ●​ Policymakers: provides an objective basis for evaluating policy impacts, and enables evidence-based decision making when balancing animal welfare with other priorities. ●​ Certification bodies: Aids in establishing objective thresholds for welfare standards 5 ●​ Advocates: allows quantitative comparison of welfare impacts of interventions and highlights high-impact opportunities to reduce animal suffering ●​ Consumers: Clarifies confusing welfare claims and certifications and empowers more informed purchasing decisions aligned with ethical values Trademark Usage and Requirements This document serves as the foundation for the trademark registration of the term "Welfare Footprint™.", a process currently underway as of 2025. The purpose of registering "Welfare Footprint™" as a trademark is to ensure that the term is used exclusively for analyses rigorously adhering to the established scientific methodology and transparency

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a trademark is to ensure that the term is used exclusively for analyses rigorously adhering to the established scientific methodology and transparency standards detailed in this document. This protects the integrity of welfare impact assessments and prevents misuse or misrepresentation of welfare impacts. Use of the term "Welfare Footprint™” is permitted only for analyses that fully comply with the methodology and transparency requirements outlined in this document. This includes adherence to the analytical components, quantification methods, and reporting standards detailed herein. Once officially registered, the term "Welfare Footprint™" must be consistently marked with the trademark symbol (™) in all communications, publications, or materials referencing this framework. The symbol must be clearly visible, especially upon first mention within any section or document. Core Framework Components The Welfare Footprint Framework (WFF) provides a structured and systematic approach to quantifying animal welfare. To do so, it focuses on affective states, prioritizing sentient organisms' subjective affective experiences, of positive and negative valence, and both of a physical and psychological nature, as key indicators of welfare. The WFF is composed of five analytical modules, visually represented in Figure 1. For simplicity, the description from this point forward will primarily focus on the analysis of negative affective experiences. However, the same principles and analytical tools apply to positive experiences, which should be incorporated for a comprehensive Welfare Footprint analysis. 6 Figure 1: Analytical Flowchart of the Welfare Footprint Framework. This diagram outlines the step-by-step process of calculating a Welfare Footprint, from describing living

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lowchart of the Welfare Footprint Framework. This diagram outlines the step-by-step process of calculating a Welfare Footprint, from describing living conditions to quantifying welfare per unit of animal product. See text for details. 7 The following are the core analytical components of the WFF: Intraspecific Analyses: focuses on quantifying the welfare of animals of a single species in the system, geography and timeframe of interest. I. Zootechnical Description: comprehensive description of the typical conditions that animals of a particular species encounter within a specific system, such as a farm, zoo, or research facility. These conditions, known collectively as Circumstances, encompass a wide range of factors that shape the animals’ lives. They include, among others, physical conditions (e.g., housing, flooring, lighting, enrichment), nutrition, social conditions, environmental factors, genetics (i.e., internal circumstances), and management (e.g., stockpersonship, routines of care, bodily mutilations). The description is hierarchical, in that Circumstances are described for each phase of life of each type of animal (referred to as ‘LifeFate’; e.g., breeders, market animals) for the system and species of interest. II. Veterinary Inventory: serves as a systematic catalog that identifies the Biological Outcomes (i.e., the direct outcomes) resulting from the Circumstances to which animals are subjected. These outcomes can be either physical -namely, observable, bodily effects that impact the animal’s physical health or physiological functioning, such as, injuries (e.g., fractures, wounds), diseases (infectious or chronic), and physiological imbalances (e.g., dehydration, malnutrition) or psychological, reflecting the processes whereby animals perceive and

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us or chronic), and physiological imbalances (e.g., dehydration, malnutrition) or psychological, reflecting the processes whereby animals perceive and process their Circumstances, such as perceptions of sensorial stimuli (e.g., noise, lighting, vibrations) and social stimuli (e.g., perception of social isolation, perception of danger). These outcomes in turn become the basis for identifying positive and negative affective experiences. III. Affective Quantification (per experience): This stage involves describing and quantifying each affective experience identified in the previous module. An affective experience is a subjective hedonic state experienced by animals, characterized by a valence (positive or negative), intensity, and duration. Each affective experience is evaluated using evidence from multiple research domains (e.g., behavior, physiology, neurology, pharmacology). Once intensity and duration are estimated, each affective experience is associated with a measure of Cumulative Pain or Cumulative Pleasure, due to the experience, within the target time period and population group. This systematic quantification provides the foundation for assessing the magnitude of welfare impacts arising from Biological Outcomes. The process for evaluating each affective experience includes four distinct analytical steps: ■​ Temporal Analysis: Each affective experience is divided into meaningful temporal segments, with each segment representing a phase during which the animal’s subjective experience remains relatively homogeneous in intensity. If the intensity of an experience changes substantially within a segment, that segment should be ideally divided into additional phases. Conversely, if consecutive segments represent 8 essentially the same affective experience

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at segment should be ideally divided into additional phases. Conversely, if consecutive segments represent 8 essentially the same affective experience (i.e., similar intensity), they should ideally be merged. For example, pain resulting from an injury could be segmented into an initial tissue damage phase, an acute inflammatory phase, and a subsequent recovery or healing phase, ensuring each phase accurately captures periods of consistent subjective experience. ■​ Evidence Documentation: For each temporal segment, all evidence that can inform the likely intensity of the affective experience is reviewed and documented. Knowledge from multiple scientific disciplines can be considered, including behavioral indicators such as activity patterns, preferences and postural changes, neurological markers like patterns of brain activity, pharmacological evidence derived from responses to pain-relieving drugs, physiological measures including stress hormones and heart rate variability, and evolutionary considerations on the adaptive nature of responses. This is often the most labor-intensive step in the process, as it requires reviewing and synthesizing a large and diverse body of evidence to justify the probabilistic assignment of intensity levels for each segment of the affective experience; ■​ Representation Using Pain-Track/Pleasure-Track: The evidence reviewed is systematically translated into standardized visual notation systems: the Pain-Track for negative experiences and the Pleasure-Track for positive experiences. These notation systems clearly depict the intensity and duration of each affective experience across the temporal segments defined. Specifically, they illustrate different intensity categories (for example, Annoying, Hurtful, Disabling, and Excruciating,

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temporal segments defined. Specifically, they illustrate different intensity categories (for example, Annoying, Hurtful, Disabling, and Excruciating, in the case of Pain), the probability distribution indicating the likelihood of each intensity category occurring within each segment, and the uncertainty ranges reflecting variability or limited evidence regarding the duration of these segments. This visual representation enhances transparency and allows for clear communication of the underlying evidence and any associated uncertainties; ■​ Calculation of Cumulative Impact: In this final analytical step, the intensity and duration data are integrated into cumulative welfare metrics, resulting in measures of Cumulative Pain [cumulative time in negative states (‘Pain’) of different intensities] or Cumulative Pleasure [cumulative time in positive states (‘Pleasure’) of different intensities] due to each affective experience. IV. Epidemiological Investigation: To quantify welfare impacts at the population level, it is necessary to estimate two key epidemiological parameters for each Affective Experience: its prevalence, defined as the proportion of animals experiencing it within the target population; and second, its occurrence, defined as how frequently affected animals endure the experience during the target period. Multiplying Cumulative Pain or Pleasure for an affective experience by its prevalence results in Cumulative Pain or Pleasure for the average population member. This is a population-level measure of the welfare impact of any affective experience that accounts for its intensity, duration, and prevalence across the 9 entire population. Additionally, the distribution of these experiences across individuals—namely, whether the welfare burden is evenly

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ce across the 9 entire population. Additionally, the distribution of these experiences across individuals—namely, whether the welfare burden is evenly spread or concentrated in particular subgroups—may also be relevant. V. Econometric Calculation (Population level): In this stage, welfare metrics previously quantified for the average population member are systematically aggregated and expressed as standardized measures per unit of product. This involves the following steps: ■​ Per Life-Fate: For each Life-Fate group (e.g., female breeders, male breeders, market animals), the total Cumulative Pain and Pleasure for the average population member are summed across all relevant Affective Experiences. This provides an overall welfare measure for an average individual within each Life-Fate; ■​ Per system: Next, welfare impacts calculated per Life-Fate are aggregated into an estimate for the entire production system. This involves weighting each Life-Fate’s welfare impact according to the proportion it represents within the production system—for instance, there may be 20 market animals for each female breeder; ■​ Per Unit of Product: Finally, system-level welfare impacts are expressed per unit of product (e.g., per egg, liter of milk, kilogram of meat). This involves incorporating productivity metrics specific to each Life-Fate (such as eggs laid per hen, milk yield per cow, or meat yield per animal), determining how many animals from each Life-Fate are required to produce a single unit of product. The resulting standardized metrics—Cumulative Pain and Cumulative Pleasure per unit of product—facilitate transparent, comparable, and meaningful welfare assessments across systems. Interspecific Weighting: accounts for potential differences in affective

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e transparent, comparable, and meaningful welfare assessments across systems. Interspecific Weighting: accounts for potential differences in affective capacity and time perception across species, as needed to compare Welfare Footprints or Cumulative Pain across species. Welfare Footprints: represent comprehensive quantitative measures of animal welfare impacts, expressed as the accumulated time animals spend experiencing negative (Cumulative Pain) and positive (Cumulative Pleasure) affective states of varying intensities. ​ This document presents the complete methodology for calculating the most comprehensive type of Welfare Footprint: the Welfare Footprint of a given amount of an animal product. This represents the highest level of integration in the framework and serves the ultimate goal of transparency for consumer information. However, it is important to emphasize that the same framework can be applied at virtually any analytical level—including the welfare impact of a single Biological Outcome, such as the pain resulting from a wound.​ Therefore, Welfare Footprints can be calculated at multiple analytical levels to inform various types of assessments and decisions, including: ●​ For a single affective experience (e.g., the Welfare Footprint of asphyxia in fish slaughter) 10 ●​ For specific practices (e.g., the Welfare Footprint of the surgical castration in piglets) ●​ For particular living conditions (e.g., the Welfare Footprint of different housing systems for laying hens) ●​ For policy interventions (e.g., the Welfare Footprint of transitioning from conventional to cage-free systems) ●​ For animal products (e.g., the Welfare Footprint of the egg or the Welfare Footprint of a kilogram of meat in certain animal production systems of a

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​ For animal products (e.g., the Welfare Footprint of the egg or the Welfare Footprint of a kilogram of meat in certain animal production systems of a certain country) Therefore, a critical aspect of all Welfare Footprint analyses is the explicit definition of analytical boundaries. These include the species examined, geographic scope, timeframe, production systems, life stages, and the affective experiences considered. Clearly delineating these boundaries is essential to ensure that comparisons of estimates are meaningful, transparent, and scientifically valid. At its core, the WFF bridges the gap between what animals feel and what can be measured. It translates subjective experiences—traditionally viewed as inaccessible—into quantifiable metrics rooted in scientific evidence. This enables rigorous evaluation of welfare outcomes and facilitates informed decision-making for producers, policymakers, certifiers, and consumers. In the following sections, we provide a detailed explanation of the analytical processes and methodological steps that underlie these calculations. 11 Intraspecific Analyses The following sections describe in detail the analytical steps involved in conducting a Welfare Footprint analysis. For more in-depth explanations, please refer to the references cited. As a reminder, for simplicity, this description focuses on the analysis of negative affective experiences. However, the same principles and analytical tools apply equally to positive experiences. Definition of Analytical Boundaries This stage establishes the scope of the analysis and defines key inclusion and exclusion parameters. These analytical boundaries determine the comparability, transparency, and interpretability of any Welfare Footprint (WF) estimate. The definition includes: At a

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tical boundaries determine the comparability, transparency, and interpretability of any Welfare Footprint (WF) estimate. The definition includes: At a minimum, the definition includes: ●​ Target species: The animal species for which the welfare assessment is being conducted. ●​ Production system or environment: The specific system or setting in which animals are kept—such as conventional intensive systems, organic systems, cage-free aviaries, extensive grazing systems, recirculating aquaculture systems (RAS), and others. These systems shape the living conditions (Circumstances) animals experience and are therefore essential to delineate from the outset. ●​ Geographic scope: The spatial domain covered by the analysis. This may range from a single farm or company to a municipality, state, country, or global region. Regional variation can dramatically affect living conditions due to differences in regulation, infrastructure, climate, and management practices. ●​ Temporal scope: The period under consideration, typically defined in years (e.g., last decade) or production cycles. Analyses often focus on recent years to reflect current or prevailing conditions, but historical or prospective timeframes may also be justified depending on the goal of analysis. ●​ Life-Fates and Life-Phases: The specific types of animals and life periods included in the analysis.Each Life-Fate is defined by its biological and economic trajectory (e.g., female breeders, market animals), while Life-Phases represent distinct stages of that trajectory (e.g., nursing, rearing, fattening, transport, slaughter, or phases such as gestation and farrowing in the case of breeders). Inclusion or exclusion of certain Life-Fates or Phases should be aligned with the purpose of the

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as gestation and farrowing in the case of breeders). Inclusion or exclusion of certain Life-Fates or Phases should be aligned with the purpose of the analysis. ●​ Affective experiences: The set of affective states considered in the quantification—e.g., pain, fear, hunger, or specific positive experiences. It is important to clarify whether the analysis includes both Cumulative Pain and Cumulative Pleasure, or focuses solely on negative welfare impacts. 12 In broader or more integrative analyses, ancillary species may be included. These are animals that, while not the primary focus of production, are involved in the system—such as cleaner fish used in salmon aquaculture or animals used as feed, bred as food for carnivorous species. Their inclusion contributes to a more comprehensive estimate of the welfare cost of a product. Even more expansively, a Welfare Footprint could, in principle, include the welfare of humans involved in the system—such as the labor force—particularly when ethical, social, or public health considerations are part of the analysis. This is a valid extension, so long as it is explicitly declared and clearly distinguished from animal welfare components. Ultimately, the transparent specification of analytical boundaries is essential to ensure interpretability and meaningful comparisons between different Welfare Footprints. This principle will be revisited in detail in the section "Welfare Footprint Expression and Notation." I. Zootechnical Description The Zootechnical Description is hierarchical by design, enabling analysts to organize complex information in a biologically meaningful way. The main levels of this hierarchy include: 1.​ Production System​ This top-level category defines the overall model of animal production, such as

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way. The main levels of this hierarchy include: 1.​ Production System​ This top-level category defines the overall model of animal production, such as conventional broiler production, organic egg farming, recirculating aquaculture systems, or extensive backyard rearing. It captures the broad structural and operational context within which animals are managed. These systems set the macro-level constraints and opportunities for welfare outcomes—shaping everything from available space and environmental conditions to access to behavioral enrichment. For analytical clarity, production systems are often subdivided into “Production Modules”, such as rearing, growing, transport, or slaughter. Each module represents a functionally and temporally distinct stage in the animal’s life and typically involves typical husbandry procedures, housing conditions, environmental stressors or welfare risks. Given their distinct biological and logistical features, it is methodologically more appropriate to analyze each module separately within the Welfare Footprint Framework.​ 2.​ Life-Fate​ At the core of this analytical structure is the concept of Life-Fates—groups of individuals within a species that share similar life trajectories and critical events [6]. In the context of animal production systems, a Life-Fate refers to a population subset that is managed for a particular biological and economic purpose. Examples include market broilers, breeder hens, sows, dairy cows, or male chicks that are culled in the first day of life. Each Life-Fate is characterized by a distinct sequence of interventions, management practices, durations of life, and end purposes—whether reproduction, meat, milk or egg production, culling, or discard. For example, in pig production, common

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s, durations of life, and end purposes—whether reproduction, meat, milk or egg production, culling, or discard. For example, in pig production, common Life-Fates include: 13 ○​ Market pigs, typically slaughtered around 4–6 months of age. ○​ Female breeders (sows), kept through multiple gestation and lactation cycles. ○​ Male breeders, usually kept longer for reproductive purposes. Life-Fates can be further disaggregated based on specific outcomes relevant to the analysis. For instance, within market pigs, a distinction might be made between those that survive to slaughter and those that die before weaning. These finer distinctions enable more accurate welfare quantification when mortality, growth performance, or management practices vary substantially within a Life-Fate. 3.​ Life-Phases​ Each Life-Fate can experience one or more biologically and operationally meaningful Life-Phases—distinct phases within the animal’s life course characterized by specific developmental stages and corresponding management conditions. Examples include the hatchery phase, suckling phase, post-weaning, growing/fattening phase, lactation, laying periods, transport and slaughter. Life-Phases are defined not merely by chronological age, but by functionally distinct features such as nutritional needs, environmental conditions, housing structure, physiological transitions (e.g., sexual maturity), and management protocols. These phases are analytically relevant because the nature, prevalence, and severity of welfare challenges can differ substantially among them. In practice, some Life-Phases may align with the boundaries of Production Modules (as described in the previous section), such as when animals are transferred from rearing to finishing environments, or from

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ies of Production Modules (as described in the previous section), such as when animals are transferred from rearing to finishing environments, or from transport to slaughter. These distinctions are not rigid biological classifications, but pragmatic subdivisions intended to enhance analytical precision and facilitate the tracking of welfare experiences across the lifespan.​ 4.​ Circumstances​ At the most granular level of the Zootechnical Description, Circumstances refer to the specific conditions and practices that animals are exposed to during each Life-Phase. The purpose of describing Circumstances in the Welfare Footprint Framework is not merely to document how animals live, but to identify which aspects of those conditions most significantly influence their (negative and positive) subjective experiences. Circumstances are not Biological Outcomes (such as diseases, infections, wounds or physiological states), but the external or internal factors that cause such outcomes. They can be broadly divided into: ●​ External Circumstances: Environmental and management-related conditions to which animals are exposed. ●​ Internal Circumstances: Intrinsic factors like genetic selection or early-life developmental trajectories. Common categories of Circumstances include: 14 ●​ Housing and spatial parameters: Cage or crate size, group size, stocking density, ventilation, flooring type, and litter condition. ●​ Social and environmental complexity: Presence or absence of environmental enrichment, isolation or group housing, crowding, or social instability. ●​ Handling and routine interventions: Frequency and method of handling, and painful procedures such as tail docking, dehorning, debeaking, castration, branding or vaccination. ●​ Feeding and

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equency and method of handling, and painful procedures such as tail docking, dehorning, debeaking, castration, branding or vaccination. ●​ Feeding and hydration: Access to food and water, nutritional content, feeding schedules, and competition. ●​ Lighting and photoperiods: Intensity, cycle duration, and disruptions to natural circadian rhythms. ●​ Climate: temperature parameters, humidity, radiance, wind conditions ●​ Air (or water) quality: levels of ammonia, dust, gasses and toxic products in the environment. ●​ Transport and slaughter procedures: Methods and duration of loading, travel, unloading, holding, stunning, and killing. Each set of Circumstances is described separately for every Life-Phase and Life-Fate, to capture the distinct experiences of different animal groups at different stages of life. This detailed mapping enables a systematic identification of which conditions are most likely to lead to negative or positive experiences. This level of resolution helps linking living conditions to Biological Outcomes. II. Veterinary Inventory The Veterinary Inventory serves as the bridge between the zootechnical realities described in the previous section and the affective experiences—such as physical and psychological Pain—that are ultimately quantified in the Welfare Footprint analysis. While the final aim of this module is to identify the most significant and welfare-relevant affective states experienced by animals, these affective states are not directly caused by the Circumstances described earlier (e.g., confinement, poor flooring, or social stressors). Instead, Circumstances first give rise to Biological Outcomes—concrete physiological, anatomical, cognitive, or neurological changes in the animal. These outcomes then become the

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give rise to Biological Outcomes—concrete physiological, anatomical, cognitive, or neurological changes in the animal. These outcomes then become the proximate triggers of affective experiences. For example: ●​ Extreme confinement may result in joint injuries or skeletal deformities, which then cause physical Pain. ●​ A lack of opportunities to express agency or lack of environmental complexity may result in cognitive perceptions of helplessness, giving rise to psychological Pain, such as frustration or depression-like states. Therefore this module has two goals: 15 (i) systematically identifying and cataloging those Biological Outcomes that arise from the Circumstances described in the Zootechnical Description, and which are most likely to produce meaningful affective impacts; (ii) identifying the resulting and relevant Affective Experiences, which will be then described and quantified in the following module. Biological Outcomes Biological Outcomes are the physiological, anatomical, neurological, or cognitive changes that result from an organism’s exposure to internal or external Circumstances. They represent the proximate biological consequences of environmental, social, genetic, and management-related conditions experienced during each Life-Phase of a given Life-Fate. These outcomes include, but are not limited to: ●​ Tissue damage and lesions (e.g., wounds, lesions, fractures) ●​ Infectious processes (e.g., infections by viruses, bacteria, ectoparasites) ●​ Physiological imbalances (e.g., dehydration, malnutrition, multiple disorders) ●​ Neurological and sensory disruptions (e.g., loss of vision, cognitive impairments) ●​ Cognitive or perceptual changes (e.g., perception of threats and opportunities) Crucially, Biological Outcomes

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ss of vision, cognitive impairments) ●​ Cognitive or perceptual changes (e.g., perception of threats and opportunities) Crucially, Biological Outcomes are not affective states themselves (such as physical pain or fear), but are instead the proximate biological events that give rise to affective experiences. Likewise, they differ from clinical signs or symptoms: for example, while coughing or nasal discharge are observable signs, the corresponding Biological Outcome might be a diagnosis such as Infectious Bronchitis. Biological Outcomes are often: 1.​ Multifactorial: A single outcome may result from multiple Circumstances. In fact, Biological Outcomes commonly occur in cascades, where initial outcomes cause subsequent ones, each affecting welfare. For example, a fractured bone (initial outcome causing pain) may cause reduced mobility (secondary outcome), preventing adequate feeding (tertiary outcome), ultimately resulting in hunger or malnutrition (further outcomes). Likewise, feather damage may impair thermoregulation, causing cold stress. Clearly mapping these cascades ensures comprehensive welfare impact analysis. 2.​ Variable in expression: Even within the same category of Biological Outcome, animals may experience widely different severities, shaped by individual traits (e.g., genetics, age, immune status) and contextual factors (e.g., social status, resource access, prior experience, environmental modulators). For instance, wounds may vary from superficial abrasions to severe tissue trauma. A bone fracture with proper alignment and healing 16 results in a fundamentally different experience than one with poor healing (malunion or non-union). Likewise, Biological Outcomes may have different trajectories, or pathways. A respiratory infection may lead to

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poor healing (malunion or non-union). Likewise, Biological Outcomes may have different trajectories, or pathways. A respiratory infection may lead to recovery, chronic respiratory distress or death. Each of these variations leads to distinct affective experiences, and thus carries different welfare implications that must be assessed independently. Accordingly, each analysis should begin by identifying the range of possible variations, which may include (a) acute episodes followed by spontaneous recovery, (b) development of chronic conditions, (c) death caused by the condition, or (d) culling due to the condition. Once possible variations types are defined, the analysis should determine the range of severities associated with each, and how these are typically classified. Where possible, it is advisable to adopt the most widely accepted severity classification schemes, ensuring the availability of data on the prevalence of different severity levels. The mapping of those possible Biological Outcomes is very interesting from several scientific perspectives. Nevertheless, it can be extensive, and therefore prioritization is essential. At least in the first approach, emphasis should be placed on high-impact conditions with putatively meaningful implications for welfare, ensuring the analysis remains comprehensive yet manageable. Several Biological Outcomes, such as immune suppression without resulting disease, or subclinical disease, can be described, but are not relevant as they do not lead to any affective consequences (i.e. they are not unpleasant or pleasant by themselves). Affective Experiences Affective Experiences are emotionally felt states that a sentient organism perceives, characterized by two core dimensions: valence and arousal. Valence refers to whether the

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e emotionally felt states that a sentient organism perceives, characterized by two core dimensions: valence and arousal. Valence refers to whether the experience is positive (e.g., joy, relief, satisfaction) or negative (e.g., pain, fear, frustration), while Arousal refers to the intensity or activation level of the experience, ranging from low (e.g., Satisfaction, Annoyance) to high (e.g., Euphoria, Disabling Pain). Affective Experiences represent the core component of animal welfare — they are not merely biological or behavioral events, but internal states felt by the organism. Within the Welfare Footprint Framework, affective experiences are the ultimate unit of analysis, because they are what animals actually experience and what welfare ultimately consists of. In the WFF, a negative affective state or experience is operationally termed ‘Pain’ [3,4], while a positive affective state or experience is termed ‘Pleasure’ [5]. It is important to remember that Biological Outcomes are not affective states in themselves — they are the physical or functional conditions that give rise to them. For example, lameness, tissue inflammation, or social isolation do not constitute suffering per se, but they can result in Pain, distress, or frustration — depending on the nature, intensity, and duration of the outcome.​ ​ 17 Veterinary knowledge, supported by other areas such as medicine and neuroscience, enables identifying how specific Biological Outcomes may give rise to one or more Affective Experiences. For instance, in addition to the acute physical pain felt by piglets due to tissue damage (a Biological Outcome), the tail docking procedure (a Circumstance) may also lead to chronic neuropathic pain (another Affective Experience) due to nerve sensitization

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come), the tail docking procedure (a Circumstance) may also lead to chronic neuropathic pain (another Affective Experience) due to nerve sensitization (Biological Outcome), or even increased fear (Affective Experience) due to the traumatic docking experience. Provided they truly represent emotional experiences (chiefly Pain and Pleasure), Affective Experiences can be described or named according to each author’s preference. Nevertheless, we recommend using a notation system (third column in Table 1) that includes as much detail as possible, even if it occasionally results in longer descriptions, to ensure clarity and precision, as follows: <Affective State> from (or due to) <Biological Outcome> caused by <Circumstance> (if the cause is known). 18 Table 1. Examples of Circumstances, Biological Outcomes, and Affective Experiences potentially endured by Egg-Laying Hens. The third column presents a recommended terminology for affective experiences that aims to be self-descriptive and transparent. This naming convention anchors affective states in their biological and contextual basis, helping avoid ambiguity. In some cases—such as in the examples—knowledge of the Circumstances may allow inference of likely Biological Outcomes. However, often the underlying causes of Biological Outcomes (e.g., specific diseases, injuries) will be uncertain or multifactorial. Circumstance Biological Outcome Affective Experience Rough handling during Fracture of the Physical pain due to fracture of the humerus catching and crating humerus caused by catching and crating High ammonia levels in Irritation of respiratory Physical pain (distress) due to difficulty poorly ventilated tissues and difficulty breathing from irritation of the respiratory tract housing breathing due to high ammonia

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s) due to difficulty poorly ventilated tissues and difficulty breathing from irritation of the respiratory tract housing breathing due to high ammonia levels Beak trimming with hot Cauterization of beak Acute pain from cauterization of beak tissues iron without anesthesia tissues Foot pad lesions from Physical pain from foot pad lesions caused by Wire flooring in cages constant pressure wire flooring in cages Moulting induced by Physical pain due to severe hunger caused by feed withdrawal for two Severe hunger two weeks feed withdrawal weeks Presence of predators Perception of danger Psychological pain (fear) from perception of due to poor enclosure due to predator danger caused by predator presence security presence Early laying onset and Keel bone fracture that Physical pain from keel bone fracture that heals high productivity heals properly properly Severe keel bone Early laying onset and Physical pain from severe keel bone fracture fracture that leads to high productivity with malunion malunion of the bone Severe infestation of red Severe skin irritation Physical pain (discomfort) from skin irritation mites in a henhouse caused by mite bites caused by red mites Feather loss, causing Physical pain (discomfort) from cold stress Injurious pecking poor insulation caused by feather loss Psychological pain (fear) from perception of Exposure to loud and Perception of threatening situation due to exposure to loud sudden noises threatening sounds and sudden noises Lack of nest for egg Thwarted expression Psychological pain (frustration) from thwarted laying of nesting behaviour nesting behaviour Isolation of conspecifics Perception of social Psychological pain from perception of social for long periods of time isolation isolation caused isolation from conspecifics 19

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s Perception of social Psychological pain from perception of social for long periods of time isolation isolation caused isolation from conspecifics 19 Association Between Circumstances, Biological Outcomes, and Affective Experiences The causal links between Circumstances, Biological Outcomes, and Affective Experiences can take various forms: ●​ One-to-One: A single Circumstance leads to one Biological Outcome and one associated Affective Experience (e.g., tail docking → tissue damage → physical pain).​ ●​ One-to-Many: A single Circumstance results in multiple Biological Outcomes (e.g., poor ventilation → respiratory infection, immune suppression, discomfort).​ ●​ Many-to-One: Multiple Circumstances contribute to a single Biological Outcome (e.g., crowding + poor sanitation → skin lesions).​ ●​ Many-to-Many: Multiple Circumstances interact to produce multiple Biological Outcomes and corresponding Affective Experiences, often through synergistic or cumulative effects. Among these, many-to-many relationships are the most prevalent in biological systems. For example, the combination of high stocking density, inadequate ventilation, and high ambient temperatures may exacerbate the incidence and severity of respiratory disease, increase physiological stress, and impair immune function—all contributing to overlapping affective burdens such as discomfort, fear, and prolonged pain. While mapping these complex interactions adds scientific value and helps identify high-leverage intervention points, attempting exhaustive characterization of all causal pathways can lead to "perfectionist paralysis"—delaying action due to the overwhelming complexity of possible interactions. Therefore, initial analyses should prioritize clarity and tractability,

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"—delaying action due to the overwhelming complexity of possible interactions. Therefore, initial analyses should prioritize clarity and tractability, focusing on the most impactful and well-supported associations. These can then be progressively refined as new data become available or as analysis goals evolve. III. Affective Quantification The development of a scientifically grounded method for quantifying affective experiences represents the cornerstone innovation of the Welfare Footprint Framework (WFF). This third module provides the systematic procedures by which both negative (Pain) [3,4] and positive (Pleasure) [5] affective states are described, analyzed, and ultimately expressed in standardized, cumulative units that can be meaningfully compared across species, production systems, 20 interventions, and timeframes. The quantification process unfolds in two distinct but interrelated phases: Temporal Description Using Notation Systems, and Calculation of Cumulative Impact (A) Temporal Description Using Notation Systems The analysis employs two complementary notation systems: the Pain-Track for negative experiences [4] and the Pleasure-Track for positive ones [5]. These notation systems allow affective states to be systematically analyzed and translated into quantitative data by dividing each experience into temporally defined segments and assigning intensity probabilities based on multidisciplinary evidence. Temporal Analysis Each affective experience is divided into meaningful temporal segments, with each segment representing a phase during which the animal’s subjective experience remains relatively homogeneous in intensity. If the intensity of an experience changes substantially within a segment, that segment should be ideally divided into additional

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geneous in intensity. If the intensity of an experience changes substantially within a segment, that segment should be ideally divided into additional phases. Conversely, if consecutive segments represent essentially the same affective experience (i.e., similar intensity), they should be merged. For example, Pain from an injury might be segmented into ​ (I) Initial tissue damage phase, (II) Acute inflammatory phase and (III) Recovery/healing phase. Rather than assigning fixed durations to each segment, the WFF uses duration ranges, which better reflect both scientific uncertainty and natural biological variation (e.g., different healing times across individuals or slower unconsciousness onset in larger fish during asphyxiation). Intensity Assessment For each temporal segment, the intensity of the affective experience is estimated using four discrete ordinal categories: ●​ Pain: Annoying, Hurtful, Disabling, Excruciating ●​ Pleasure: Satisfying, Joyful, Euphoric, Blissful These definitions are intended to be stable over time, though refinements may occur based on new scientific evidence or expert consensus. All definitions are publicly maintained for transparency and reproducibility: ●​ Pain Intensity Definitions: https://welfarefootprint.org/pain-intensities ●​ Pleasure Intensity Definitions: https://welfarefootprint.org/pleasure-intensities Evidence-Based Estimation For each time segment, existing evidence that may indicate the intensity of the experience is reviewed and documented, including behavioral indicators (e.g., changes in activity patterns, 21 posture, facial expressions), physiological responses (e.g., stress hormones, heart rate), neurological markers (e.g., brain activity patterns), pharmacological evidence (e.g., response to

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gical responses (e.g., stress hormones, heart rate), neurological markers (e.g., brain activity patterns), pharmacological evidence (e.g., response to pain-relieving drugs) and evolutionary considerations (e.g., adaptive value of pain responses in each case). The framework emphasizes using multiple complementary indicators1 rather than relying on any single measurement, as each indicator provides only partial information about an animal's affective state. This multidisciplinary evidence is then evaluated (Box 1) against the criteria that define each intensity category. Each level of intensity is treated as a hypothesis, and evidence is weighed for or against it. Because certainty is rarely achievable, probabilities are assigned to each category within a segment. For example, if the available evidence during the acute inflammatory phase of an injury suggests the Pain could be either Hurtful or Disabling, but cannot clearly distinguish between them, a probability split such as 50% Hurtful and 50% Disabling may be assigned. Box 1. How the WFF uses evidence to estimate intensity and duration This box describes how scientific evidence is translated into final welfare estimates. It is important to emphasize that the translation of indirect evidence into inferred affective states is inherent to all animal welfare assessments. Behavioral indicators (e.g., vocalizations, postures, preferences, activity), physiological measures, brain activity patterns, and responses to pain-relieving drugs, are widely used to infer states like pain and positive emotions. Estimating their intensity and duration is a common challenge, addressed by most methods using expert judgment of indirect and often scarce evidence. For example, EFSA’s risk assessment model uses literature reviews and

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sed by most methods using expert judgment of indirect and often scarce evidence. For example, EFSA’s risk assessment model uses literature reviews and expert elicitation to assign intensity scores to welfare consequences based on their perceived pain and distress [7]. In the Welfare Quality® Protocol [8], experts estimate the severity of different issues on a 0 to 100 scale, which are then aggregated into composite scores. In the Five Domains Model [9], experts grade welfare compromises on a scale from A to E (low to high intensity negative affects), as based on their evaluation of existing indicators. In the WFF, the subjectivity of these inferences is constrained through a structured and transparent evidence-based approach. The following steps are conducted for each temporal segment within a Pain- or Pleasure-Track: Each intensity level is framed as a hypothesis. In every Pain- or Pleasure-Track, the four intensity categories are treated as competing hypotheses during any given time-segment. In this way, supporting and contradictory evidence for all four intensities can be evaluated in a transparent way. Multidisciplinary Evidence Collection and Documentation. Existing knowledge and proxy indicators from multiple disciplinary perspectives is 1 For a distinction between welfare metrics and indicators, see [6] 22 reviewed and documented: Behaviour – e.g. changes in activity levels, posture, mobility, play suppression, withdrawal, QBA scores, grimace scales, choice/avoidance tests, preference and motivational tests. Physiology – e.g. heart-rate variability, levels of stress hormones, immune and metabolic markers. Neurology – e.g. density of innervation, nociceptive pathways, EEG/fMRI patterns. Evolutionary insights – e.g. the extent to which pain and pleasure

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. Neurology – e.g. density of innervation, nociceptive pathways, EEG/fMRI patterns. Evolutionary insights – e.g. the extent to which pain and pleasure intensity would need to be intense for adaptive functioning and survival. Pharmacological responses – e.g. type of pain-relieving drug and dose needed for behavior to resume to normal. Constrained subjectivity in expert elicitation ​ ​ In translating evidence to estimates of intensity and duration, the WFF constrains subjectivity by forcing experts to: 1.​ justify estimates based on the documented evidence, citing the studies or reasoning underlying every estimate; 2.​ make uncertainties and disagreements explicit by using uncertainty ranges for durations and probabilities for intensities. Allowing for the representation of uncertainty and variability​ ​ Due to inherent uncertainties associated with lack of data and knowledge and the variability with which animals experience different conditions (e.g. some animals may feel pain more intensely or take longer to recover), intensity estimates are expressed as probabilities (e.g., if evidence is insufficient to differentiate between two intensity categories, a 50% probability is assigned to each). These probabilities serve two complementary purposes: ●​ Epistemic uncertainty: Reflecting the confidence that the experience falls within a given category due to limited or ambiguous evidence. ●​ Aleatory variability: Representing real individual variation across a population (e.g., some animals feeling Hurtful pain while others feel Disabling pain from the same condition). Accounting for temporal variations keeps evidence biologically coherent. The WFF acknowledges that intensities fluctuate over time (e.g., sharp pain dulling during healing), and that

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ns keeps evidence biologically coherent. The WFF acknowledges that intensities fluctuate over time (e.g., sharp pain dulling during healing), and that for evidence to be informative it must be properly matched to the different moments of the experience (e.g., using the presence of inflammatory markers as indicators of likely pain intensity only in the inflammatory phase). This 23 prevents “evidence leakage” that could otherwise bias estimates. Iterative updates and version control. All estimates and supporting evidence are transparently documented in publicly accessible documents or databases. This approach allows periodic updates as new data becomes available, akin to updating a living systematic review. Thus, the WFF goes further in constraining subjectivity by making assessments transparent, evidence-based, and open to scrutiny. When data is unavailable, the WFF offers a structured method for generating estimates—grounded in the same expert interpretation of the literature used by other frameworks, but with transparency as to the data available, or lack thereof, supporting these estimates. Notation Systems for Describing Affective Dynamics Pain-Track and Pleasure-Track are standardized notation tools developed within the Welfare Footprint Framework to describe and quantify the temporal dynamics of animals’ affective experiences (not Biological Outcomes or Circumstances). They are structured as matrices where each column represents a biologically meaningful time segment, and each row corresponds to a defined intensity level of Pain or Pleasure. These notation tools allow for the assignment of probabilities to each intensity level within each segment, capturing both uncertainty in assessment and inter-individual variation in how animals experience those

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s to each intensity level within each segment, capturing both uncertainty in assessment and inter-individual variation in how animals experience those states. The Pain-Track includes four levels of negative affect, from Neutral to Excruciating, while the Pleasure-Track mirrors this ordinal structure for positive affect, ranging from Neutral to Blissful. Together, they form a standardized language to describe affective transitions with temporal and intensity resolution. Next are examples of a Pain-Track and a Pleasure-Track illustrating how experiences are decomposed into time segments, with probability distributions assigned to different intensity categories in each temporal segment. 24 Pain-Track — Hypothetical timeline of the pain intensity endured by commercial broilers affected by pulmonary hypertension (a condition involving elevated blood pressure in the pulmonary arteries, often leading to right-sided heart failure and fluid accumulation in the abdomen — ascites): Phase I​ Phase II​ Phase III​ Phase IV​ (Hypoxaemia) (Pulmonary (Ascites) (Cardiac failure) hypertension) Excruciating 1% 50% Disabling 10% 25% 74% 50% Hurtful 80% 50% 25% Annoying 10% 25% Neutral Estimated Duration 1-2 weeks 1-3 weeks 2-5 days 0.5-1.5 min … in Hours 168-336 168-504 48-120 0.017 … in Hours - sleep time 98-280 98-420 28-100 0.017 (4 to 10 hrs/day) ​ ​ Pleasure-Track — Hypothetical evolution of pleasure intensity during a play bout in calves, from initiation through resolution: Phase I Phase II. Phase III Phase IV Phase V (Exploration) (Escalation) (Peak) (Resolution) (Relaxation) Blissful Euphoric 20% 60% 20% Joyful 20% 60% 40% 40% 20% Satisfying 60% 20% 40% 80% Neutral 20% Estimated Duration 10-30 sec 10-300 sec 5-40 sec 20-100 sec 2-10 min By segmenting each

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ful 20% 60% 40% 40% 20% Satisfying 60% 20% 40% 80% Neutral 20% Estimated Duration 10-30 sec 10-300 sec 5-40 sec 20-100 sec 2-10 min By segmenting each experience into time intervals and assigning probabilistic estimates to each intensity level, the Pain-Track and Pleasure-Track enable a scientifically grounded, transparent quantification of affective states. These estimates are continuously updated as new evidence becomes available, ensuring that welfare assessments reflect the most accurate understanding of animal experiences. Interactions among Affective States While the framework enables the systematic analysis of individual affective experiences, in biological reality, these states often interact in complex and non-additive ways. Early traumatic experiences, for example, can alter an animal’s sensitivity to pain and coping capacity later in life. Similarly, the co-occurrence of different challenges—such as injury and infection—may lead to compounded effects that exceed the sum of their individual impacts. 25 The Welfare Footprint Framework accommodates such interactions through two complementary mechanisms: 1.​ Incorporation via Evidence Indicators:​ Because intensity estimates are based on behavioral, physiological, neurological, and other empirical indicators, any synergistic effects are inherently captured if reflected in the empirical data used to inform the estimates. For instance, if animals subjected to a second injury display more severe indicators than expected from the first, this will be reflected in the higher probabilities assigned to more intense categories in subsequent Pain-Track segments. Likewise, if early stressors sensitize animals to subsequent pain episodes, or impair healing, these changes can be incorporated through updated

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ents. Likewise, if early stressors sensitize animals to subsequent pain episodes, or impair healing, these changes can be incorporated through updated evidence (e.g., longer healing times) for each time segment.​ 2.​ Dynamic Adjustments within Notation Systems:​ The Pain-Track and Pleasure-Track can be adapted over time to reflect changes in sensitivities, coping capacities, physiological vulnerabilities, or emotional reactivity. For prolonged or repeated experiences, the intensity distributions in later segments can be adjusted to account for processes like sensitization (increased response to repeated exposure) or habituation (reduced response). In this way, the framework remains flexible and biologically coherent, capable of capturing the evolving affective landscape of individual animals over time. This capacity to reflect interaction effects, while preserving the structured and evidence-based nature of the framework, is essential for accurately portraying complex welfare impacts. Handling Limited or Conflicting Evidence A key strength of the Welfare Footprint Framework is its transparent and structured approach to handling limited or conflicting evidence. Rather than letting these limitations prevent assessment or forcing arbitrary choices, the methodology provides clear protocols for documenting uncertainty and knowledge gaps. When evidence regarding intensity or duration is sparse, ambiguous, or contradictory, these uncertainties are openly captured using probability distributions for intensity and duration ranges for temporal segments. For instance, in the unlikely event that no information was available to inform the intensity of a negative Affective Experience, each intensity category (from Neutral to Excruciating) would be assigned a 20% probability.

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o inform the intensity of a negative Affective Experience, each intensity category (from Neutral to Excruciating) would be assigned a 20% probability. This approach avoids masking gaps in knowledge and makes the strength and limitations of each assessment explicit. This transparency serves several purposes: it ensures that users understand the evidentiary basis—and its limits—behind each estimate, it highlights priority areas for future research, and it 26 allows decision-makers to weigh welfare metrics with a clear understanding of the robustness of underlying data. Integration with Computational and AI Tools The Welfare Footprint Framework (WFF) is particularly well-suited to benefit from recent advances in artificial intelligence (AI), especially Large Language Models (LLMs). As noted by Nobel Laureate Demis Hassabis [10], problems most amenable to AI solutions typically involve: A.​ Massive combinatorial search spaces, B.​ A well-defined objective function, and C.​ Access to large datasets or an efficient simulator. The Welfare Footprint Framework (WFF) is particularly well-suited to leverage recent advancements in Large Language Models (LLMs) and other artificial intelligence (AI) tools. As noted by Nobel Laureate Demis Hasabis, the types of problems best suited to AI solutions are those that require: (1) massive combinatorial search spaces, (2) a clear objective function (metric) to optimize and (3) large datasets and/or an efficient simulator. The WFF aligns with all three. It requires exploring a vast space of potential animal experiences across species, life-stages, production conditions, and interventions. It also features a clear objective metric—cumulative time spent in affective states of defined intensity—and leverages extensive, though

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nterventions. It also features a clear objective metric—cumulative time spent in affective states of defined intensity—and leverages extensive, though heterogeneous, scientific evidence. While these technologies enhance throughput and coverage, final interpretation and probabilistic judgments will remain grounded in expert review. Human evaluators are essential for judging evidence quality, integrating contextual knowledge, and assigning and validating final probability distributions. When effectively integrated, AI tools can dramatically accelerate the mapping and quantification of affective states across production systems. What previously might have required decades of manual synthesis can now be approached in years, at a fraction of the cost and time—greatly expanding the reach, granularity, and utility of the WFF in research, regulation, and industry transformation [11]. (B) Calculation of Cumulative Affect Cumulative Pain and Cumulative Pleasure are the core quantitative outputs of the Welfare Footprint Framework (WFF). They represent the total affective burden—negative or positive—experienced by animals within a given analytical boundary, such as a particular affective episode, life-phase, production system, or population. These metrics are derived directly from the Pain-Track and Pleasure-Track, which describe the temporal evolution and intensity profile of individual affective states based on multidisciplinary evidence. 27 Cumulative Pain (or Cumulative Time in Pain of Different Intensities) quantifies the total time animals are estimated to spend in each category of negative affective intensity (Annoying, Hurtful, Disabling, Excruciating). Cumulative Pleasure (or Cumulative Time in Pleasure of Different Intensities) similarly quantifies time spent

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ying, Hurtful, Disabling, Excruciating). Cumulative Pleasure (or Cumulative Time in Pleasure of Different Intensities) similarly quantifies time spent in positive affective states (Satisfying, Joyful, Euphoric, Blissful). These cumulative metrics allow the burden or benefit of affective experiences to be expressed in standardized, interpretable time-based units, such as hours per animal or hours per kilogram of product—enabling comparisons across systems, practices, and species. From Tracks to Cumulative Metrics Once a Pain-Track or Pleasure-Track is defined, calculating cumulative time at each intensity becomes a straightforward arithmetic operation. For each temporal segment: 1.​ Estimate the time range of the segment (typically in hours), adjusting if necessary (e.g., excluding sleep periods if evidence supports reduced affective processing during sleep). 2.​ Multiply the estimated duration by the probability assigned to each intensity level in that same segment. 3.​ Sum the products across all segments, for each intensity category, to obtain the total time spent in each intensity category as a result of the target affective experience. Cumulative Pain Table – Example: Fatal Case of Pulmonary Hypertension in Broilers. Cumulative time spent in each pain intensity category for each temporal segment, and total (last column) Cumulative time in Pain, based on the Pain-Track introduced in the previous section. Calculations were obtained by multiplying the estimated duration of each segment (in hours, excluding sleep time) by the probability assigned to each pain intensity within that segment. All values are expressed as ranges (in hours) to reflect both biological variation and uncertainty in the supporting evidence. Hypoxaemia Pulmonary Ascites (fluid Severe

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essed as ranges (in hours) to reflect both biological variation and uncertainty in the supporting evidence. Hypoxaemia Pulmonary Ascites (fluid Severe cardiac Cumulative (low blood hypertension transudation failure (death) Pain (hours) oxygen) into abdomen) Excruciating 0.28-1 0.0085 0.29-1 Disabling 9.8-28 24.5-105 20.72-74 0.0085 55-207 Hurtful 78.4-224 49-210 7-25 134-459 Annoying 9.8-28 24.5-105 34-133 28 IV. Epidemiological Investigation Having identified the relevant Circumstances, their resulting Biological Outcomes, and the Affective Experiences they generate—and having quantified each of those experiences in terms of intensity and duration for affected individuals—the next step is to understand how widely each experience is distributed across the population. This epidemiological module enables the WFF to move from the measurement of individual-level to population-level welfare impacts. The Epidemiological investigation serves two functions within the WFF: 1.​ It determines how frequently each Biological Outcome occurs in affected individuals (e.g., how many times a respiratory infection is typically experienced in a broiler’s life), enabling precise calculation of total affective burden, of each outcome, per individual. For example, if an injury causes 8 hours of Hurtful pain and is experienced on average twice over the period of interest, Cumulative Pain from such injury, for affected individuals, will correspond to an average of 16 hours of Hurtful pain​ 2.​ It estimates the prevalence of each outcome—how many individuals within the target population are affected—allowing us to move from individual Cumulative Pain or Pleasure to population-level welfare assessments. This is done by multiplying Cumulative Pain or Pleasure for an affective

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dividual Cumulative Pain or Pleasure to population-level welfare assessments. This is done by multiplying Cumulative Pain or Pleasure for an affective experience by its prevalence in the population, resulting in Cumulative Pain or Pleasure for the average population member. For example, if a bone fracture causes 10 hours of Disabling Pain and affects 60-80% of individuals in the target group (e.g., laying hens in cage-free aviary systems at a global level), the average member of this population is said to experience 6-8 hours of Disabling Pain from this fracture. Rather than using single point estimates, prevalence should also be expressed as a range that captures both: (i) natural variation in prevalence across different systems and populations within the analytical boundaries and (ii) uncertainty in the prevalence estimates themselves due scarcity of data. Moreover, this module provides the basis for exploring ethical dimensions: whether suffering is concentrated in a few individuals or more evenly spread across the population. While total Cumulative Pain may be equal in two systems, its distribution may vary dramatically—raising important questions about fairness, equity, and intervention priorities. V. Econometric Calculation This final analytical phase integrates the cumulative affective burdens experienced by animals into system-level outputs. It does so by aggregating the welfare impacts of affective experiences across Life-Fates and standardizing them by productivity metrics. The outcome is a 29 set of powerful and versatile metrics, the Welfare Footprint per production system and per unit of animal product—that enable transparent and meaningful comparisons across species, production models, and consumption patterns.. Cumulative Pain and Pleasure for Each

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that enable transparent and meaningful comparisons across species, production models, and consumption patterns.. Cumulative Pain and Pleasure for Each Life-Fate Each Life-Fate (e.g., market animal, breeder, culled individual) is associated with a unique set of affective experiences. The total Cumulative Pain and Cumulative Pleasure for that Life-Fate is calculated by summing the Cumulative Pain and Cumulative Pleasure of each affective experience (already adjusted for prevalence), across all relevant Life-Phases. For example, for egg-laying hens, this step would involve adding up Cumulative Pain from each and every experience considered, such as the pain and discomfort from cold stress, keel bone fractures, reproductive diseases, hunger, fear and frustration from deprivation of motivated behaviours. This level of analysis is valuable in its own right. For example, it brings to light which Life-Fates contribute most to a production system’s total welfare burden, and thus where interventions may yield the greatest improvements. Cumulative Pain and Pleasure for the Average Individual in a System To compute the Welfare Footprint of the average individual across multiple life fates in a system, Cumulative Pain and Pleasure estimates from all relevant Life-Fates are aggregated. To this end, each Life-Fate is weighted by its proportional representation within the system. For example, in a system with 20 market pigs for every breeder sow, the sow's contribution to the total Cumulative Pain would represent approximately 1/21 of the weighted average. This yields a system-level welfare footprint per average animal, which can be compared across production models, regions, or timeframes. This aggregate metric serves as a foundational tool for benchmarking welfare performance

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be compared across production models, regions, or timeframes. This aggregate metric serves as a foundational tool for benchmarking welfare performance between systems; setting regulatory thresholds or certification standards, and monitoring the impact of interventions at the system level. Welfare Footprint: Cumulative Pain and Pleasure per Unit of Product The final and most widely usable expression of the WFF integrates welfare data with productivity metrics to yield Cumulative Pain and Pleasure per unit of product. This involves dividing the system-level cumulative metrics by outputs such as kilograms of meat per animal, liters of milk per cow per lactation, or dozens of eggs per hen per cycle. For example, 7.2 hours of Disabling Pain per kilogram of pork, or 45 minutes of Satisfying Pleasure per dozen eggs. Welfare Footprints enable: 30 1. Cross-System Comparisons. This enables ethical and policy comparisons between high- and low-yield systems. For instance, a system that reduces pain per animal but requires more animals to meet demand may not outperform another system on a per-product basis. Standardizing to product units reveals such trade-offs. 2. Cost-Effectiveness and Policy Guidance. Donors, funders, and policymakers can assess which reforms yield the greatest welfare impact per dollar or per kilogram—helping to prioritize scalable, higher-impact interventions. 3. Consumer Engagement. Most consumers purchase by volume or weight. By expressing welfare impacts in these terms, the WFF bridges the gap between consumer values and practical choices—empowering individuals to make ethically informed decisions based on transparent, comparable welfare metrics. Interspecific Scaling The Welfare Footprint Framework (WFF) uses a universal metric—time spent in

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ns based on transparent, comparable welfare metrics. Interspecific Scaling The Welfare Footprint Framework (WFF) uses a universal metric—time spent in affective states of varying intensities—to quantify welfare impacts. Because affective experiences such as Pain and Pleasure lie at the core of sentient experience, this metric provides a common currency for evaluating welfare across contexts, life histories, and even species. It holds the potential to compare welfare burdens in a biologically meaningful way across diverse taxa, including humans. However, applying a universal scale introduces two critical challenges: (1) differences in hedonic capacity across species, and (2) differences in time perception. Hedonic Capacity and the Use of an Absolute Scale Different species may vary in their hedonic capacity [12,13] —that is, their biological potential to experience the intensity of affective states such as Excruciating Pain or Blissful Pleasure. These potential differences may stem from divergences in neural architecture (e.g., complexity of nociceptive systems or limbic structures), cognitive capacities (such as awareness, memory, or reflective processing), or evolutionary pressures that shaped how strongly different organisms are motivated to act on affective cues. At present, however, scientific knowledge on interspecific differences in hedonic capacity is limited and inconclusive. While there may be neurological, cognitive, or evolutionary reasons to expect such differences, questions about the nature and magnitude of these differences remain among the most intriguing and ethically significant in biology, neuroscience, and philosophy. Given this uncertainty, the WFF adopts a provisional but transparent convention: affective intensities are defined as absolute,

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ience, and philosophy. Given this uncertainty, the WFF adopts a provisional but transparent convention: affective intensities are defined as absolute, cross-species categories, anchored in the human capacity to feel [14] (the only possible reference point). In this framework one hour of Excruciating pain in a 31 lobster is treated as equivalent to one hour of Excruciating pain in a human. Differences in Time Perception Across Species In addition to differences in intensity, species may also differ in their subjective experience of time. If some animals experience time as passing more slowly (e.g., due to faster neural processing or metabolic rates), then the same clock-time experience may feel longer to them, potentially increasing the cumulative burden of pain. For example, two hours of painful confinement might be subjectively longer for a fast- than for a slow-living species. This dimension of interspecific comparison is known as subjective time scaling. Optional Correction Factors In recognition of these unknowns, the WFF allows for the use of optional correction factors in the final welfare estimates. These factors enable: ●​ The incorporation of emerging scientific evidence on interspecific hedonic differences, ●​ The accommodation of ethical positions or philosophical worldviews that assign different weights to different species. For instance: if it is believed (based on evidence or reasoned judgement) that mice have half the hedonic capacity, or moral weight, of humans, then their Cumulative Pain values could be multiplied by 0.5. Crucially, any use of correction factors must be made explicit in reporting, to ensure transparency and to allow readers to make their own normative interpretations. These factors are not inherent to the WFF itself, but

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orting, to ensure transparency and to allow readers to make their own normative interpretations. These factors are not inherent to the WFF itself, but represent a flexible layer for ethical pluralism and evolving scientific understanding. In summary, while the WFF currently treats affective time units as species-invariant, it provides a clear and transparent pathway for incorporating species-specific differences in both affective capacity and time perception, should the evidence base or ethical frameworks require it. Welfare Footprint Expression and Notation Fundamental Requirements To ensure that Welfare Footprint estimates are both interpretable and comparable, each complete Welfare Footprint expression must include three essential elements: Identification of the Target of Analysis 32 This element specifies what is being assessed. It may include the type of product (e.g., meat, milk, eggs, wool), the species, the production system (e.g., conventional, organic, pasture-based), and the unit of measurement (e.g., per kilogram, per liter, per individual animal). This identification provides the basic context for any welfare analysis, ensuring clarity for stakeholders. Some examples include: ●​ Welfare Footprint of Eggs from Conventional Cages (per egg) ●​ Welfare Footprint of Chicken Meat from Conventional (intensive) systems (per kilogram) ●​ Welfare Footprint of Milk from Dairy Cows in Intensive Systems (per liter) ●​ Welfare Footprint of Intensively farmed Tilapia in Brazil (per fish) ●​ Welfare Footprint of Pork from Conventional (intensive) System in Spain (per kilogram) ●​ Welfare Footprint of Wool from Sheep in Pasture-Based Systems (per kilogram)​ Cumulative Pain and Cumulative Pleasure Estimates These are the core metrics of the Welfare

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f Wool from Sheep in Pasture-Based Systems (per kilogram)​ Cumulative Pain and Cumulative Pleasure Estimates These are the core metrics of the Welfare Footprint Framework. They describe the total time that animals spend in each intensity category of Pain or Pleasure, accumulated over the relevant phases of life and expressed in standardized time units (typically hours or minutes). Rather than aggregating intensity categories into a single welfare score, the WFF maintains distinct time values for each intensity level. This preserves the ethical and biological distinction between different kinds of suffering and enjoyment. Explicit Definition of Analytical Boundaries It is critical to clearly state the scope of the analysis, including the Life-Fates considered (e.g., market animals, breeding stock, discarded individuals), Life-Phases (e.g., rearing, transport, slaughter) and set of Affective Experiences measured. Clearly specifying these boundaries ensures that comparisons between different Welfare Footprints are meaningful and fair. Without this transparency, even similar-looking metrics might reflect incommensurable assumptions. For instance, comparing the Welfare Footprint of eggs from two production systems might be meaningful if both estimates include the same Life-Fates (laying hens, parent stock, and male chicks), similar Life-Phases (e.g., from birth through end of life), and sets of Affective Experiences. Example – Pig Production: ●​ Life-Fates: Market Pigs, Female Breeders, Male Breeders ●​ Life-Phases: Nursing, Transport to Farm, Rearing, Growing, Transport to Abattoir, Stunning ●​ Affective Experiences: 33 ○​ Negative (Pain): Physical Pain from surgical castration, tail docking, ear notching, lameness, respiratory disease, infectious

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tive Experiences: 33 ○​ Negative (Pain): Physical Pain from surgical castration, tail docking, ear notching, lameness, respiratory disease, infectious diarrhea, skin wounds, tumors, abscesses, heat stress, hunger, crushing, and fractures; Psychological Pain from deprivation of motivated behaviours, fear, boredom, and social stress. ○​ Positive (Pleasure): Physical Pleasure from preferred foods; Psychological Pleasure from social bonding, play behavior, and maternal care. Figure 2 presents a possible format for expressing Welfare Footprint estimates that integrates the three requirements described above. This proposed visualization demonstrates how the identification of the analysis target, disaggregated Cumulative Pain and Pleasure estimates, and explicit analytical boundaries could be combined into a single comprehensive presentation. While the specific format may vary depending on the context and audience, any expression of a Welfare Footprint must include these essential elements to ensure transparency and comparability across assessments. Figure 2: Example of Notation for Welfare Footprint Estimates for a hypothetical scenario (e.g., the Welfare Footprint of one unit of a product). 34 Transparency Requirements To preserve the scientific rigor, credibility, and comparability of all analyses conducted under the Welfare Footprint Framework (WFF), the following transparency standards must be met in any presentation or publication that uses the “Welfare Footprint” designation. These requirements ensure that users—whether scientists, policymakers, industry actors, or the general public—can critically evaluate the scope, methods, and strength of the evidence supporting each assessment. Boundary Documentation All analyses must clearly define the analytical

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te the scope, methods, and strength of the evidence supporting each assessment. Boundary Documentation All analyses must clearly define the analytical boundaries, including the Life-Fates (e.g., market animals, breeders, culled individuals), Life-Phases (e.g., rearing, transport, slaughter), Affective Experiences included (e.g., Pain due to injury, Pleasure from social play), and any notable exclusions from the analysis. Evidence Transparency Analyses must provide access to the scientific evidence and methodological justifications used to estimate the intensity and duration of affective experiences. This includes ample documentation and citation of the evidence and knowledge used to support estimates of intensity, duration and prevalence. Uncertainty Representation To avoid overstating precision, all quantitative results (e.g., Cumulative Pain or Pleasure) must be expressed as ranges or probability distributions rather than single-point estimates. This requirement applies to all temporal durations, intensity probabilities, occurrence frequencies, and prevalence estimates. Methodological Documentation Analyses must include or make available all relevant methodological details, including: (i) Pain-Track and Pleasure-Track diagrams, showing time segments and assigned probabilities for each intensity category, (ii) the prevalence estimates and occurrence assumptions used for each Biological Outcome, (iii) any interspecific scaling factors applied (e.g., hedonic capacity corrections), and (iv) all productivity and mortality parameters used in the final Welfare Footprint calculations. Complete Results Presentation 35 Selective reporting is not permitted. All results—including those that may reflect minimal impact or contradict prior expectations—must be disclosed to

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elective reporting is not permitted. All results—including those that may reflect minimal impact or contradict prior expectations—must be disclosed to ensure balanced interpretation, avoid bias in representation, and enable reproducibility and independent evaluation. Expression Flexibility While these elements are essential, the methodology allows flexibility in how they are presented. It also recognizes that different contexts may require distinct presentation formats. For scientific publications, a detailed technical format might be appropriate, whereas for consumer communication, a simplified format with digital access to complete documentation may be more suitable. In all cases, the fundamental elements must be either directly presented or easily accessible through referenced documentation. The most challenging information to convey to different audiences is related to the boundaries of analysis. This information is complex not only because it can be extensive but also due to its nested structure: for each Life-Fate, multiple Life-Phases may be considered, while affective experiences can span several Life-Phases. To manage this complexity when it is impractical, the complete information can be made accessible via a link or QR code, with only a textual summary or graphic representation provided for clarity. 36 Summary of Methodological Strengths The Welfare Footprint Framework embodies methodological strengths that make it particularly well-suited for quantifying animal welfare. These strengths address challenges that have historically limited welfare assessment: the need to capture the full spectrum of animal experiences, to transparently handle scientific uncertainty, and to produce metrics that are practically applicable. Together, these features enable the

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periences, to transparently handle scientific uncertainty, and to produce metrics that are practically applicable. Together, these features enable the WFF to fulfill its purpose—providing comprehensive, transparent, and comparable measurements of animal welfare across diverse contexts. Comprehensive Domain Coverage The WFF enables considering affective experiences that arise from all recognized domains of animal welfare, including nutrition, environment, health, behavior, and cognitive or emotional state. This ensures that the full spectrum of welfare-relevant conditions is addressed—not just biological functioning. Comprehensive System Coverage The WFF enables considering affective experiences within a system as broadly defined as needed, including several types of Life-Fates (all those directly and indirectly involved in an environment or production chain), in all their Life-Phases (from birth to slaughter), including all possible Affective Experiences, in any geographic and temporal scale. Completeness in Affective Coverage The framework integrates both positive and negative affective experiences, recognizing that welfare is shaped not only by suffering but also by the presence of positive states. It includes both physical and psychological experiences, allowing for a biologically and ethically comprehensive representation of animal welfare. Evidentiary Standards and Multidisciplinarity WFF assessments are based on structured reviews of multidisciplinary evidence, including behavioral, physiological, neurological, pharmacological, and evolutionary knowledge. Estimates of intensity and duration of affective experiences are grounded on evidence, with evidence-to-judgment pathways clearly documented. Evidence Quality and Gaps The framework is anchored in available

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nces are grounded on evidence, with evidence-to-judgment pathways clearly documented. Evidence Quality and Gaps The framework is anchored in available scientific knowledge but explicitly exposes uncertainty or poor evidence. This serves both to bound confidence in current assessments and to highlight 37 areas where further research is needed. Where knowledge is incomplete, expert judgment is possible—but must be clearly documented and justified. Transparency and Traceability All assumptions, data sources, probability estimates, and methodological choices are fully documented and publicly accessible. This enables scientific scrutiny, reanalysis with updated evidence, sensitivity analysis, clear communication with diverse stakeholders, and consistency across applications. Uncertainty Management Rather than obscuring uncertainty, the framework explicitly incorporates it into all stages of analysis. Probabilistic treatment is used for intensity estimates (e.g., likelihood of Hurtful vs. Disabling Pain), duration ranges, occurrence frequencies, and prevalence estimates. Normative Flexibility The WFF maintains intensity categories in a disaggregated form, enabling users to apply their own ethical weighting systems (e.g., prioritizing elimination of Excruciating Pain), explore different trade-offs (e.g., between mild suffering and intense pleasure), or create custom indices (e.g., “severe suffering hours”) when appropriate for policy or economic analyses. The framework does not impose a moral equivalence between intensities or between Pain and Pleasure, acknowledging that these judgments remain ethically contested. Instead, it provides the transparency and modularity needed to support a diversity of value systems. 38 References 1. ​ Schuck-Paim C, Alonso WJ.

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ted. Instead, it provides the transparency and modularity needed to support a diversity of value systems. 38 References 1. ​ Schuck-Paim C, Alonso WJ. Quantifying Pain in Laying Hens: A blueprint for the comparative analysis of welfare in animals. Independently published. https://tinyurl.com/bookhens; 2021. 2. ​ Schuck-Paim C, Alonso WJ. Quantifying Pain in Broilers. Independently published. https://tinyurl.com/bookhens; 2022. 3. ​ Alonso WJ, Schuck-Paim C. The Comparative Measurement of Animal Welfare: the Cumulative Pain Framework. In: Schuck-Paim C, Alonso WJ, editors. Quantifying Pain in Laying Hens. Independently published. https://tinyurl.com/bookhens; 2021. 4. ​ Alonso WJ, Schuck-Paim C. Pain-Track: a time-series approach for the description and analysis of the burden of pain. BMC Res Notes. 2021;14: 229. 5. ​ Alonso WJ, Schuck-Paim C. A framework for quantifying positive animal welfare in individuals and populations. OSF; 2024. doi:10.17605/OSF.IO/MDGJR 6. ​ Alonso WJ, Schuck-Paim C. Metrics vs. Indicators: Clarifying Essential Concepts in Animal Welfare Assessment – Welfare Footprint Institute. 2023 [cited 24 Feb 2025]. Available: https://welfarefootprint.org/2023/05/31/welfare-metrics-vs-welfare-indicators/ 7. ​ EFSA Panel on Animal Health and Welfare (AHAW). Guidance on risk assessment for animal welfare. EFSA Journal. 2012;10: 2513. 8. ​ Welfare Quality Consortium. Welfare Quality Assessment protocol for pigs (sows and piglets, growing and finishing pigs). Lelystad, Netherlands; 2009. Available: http://www.welfarequalitynetwork.net/media/1018/pig_protocol.pdf 9. ​ Mellor DJ. Operational Details of the Five Domains Model and Its Key Applications to the Assessment and Management of Animal Welfare. Animals (Basel). 2017;7.

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J. Operational Details of the Five Domains Model and Its Key Applications to the Assessment and Management of Animal Welfare. Animals (Basel). 2017;7. doi:10.3390/ani7080060 10. ​Hassabis D. Accelerating scientific discovery with AI. Sweeden: Youtube; 16 Dec 2024 [cited 23 Feb 2025]. Available: https://www.youtube.com/watch?v=yxAJohm0l_g 11. ​Alonso WJ, Schuck-Paim C. Can AI power the Global Mapping and Quantification of Animal Suffering? The Pain Atlas Project – Welfare Footprint Project. 2024 [cited 11 Nov 2024]. Available: https://welfarefootprint.org/2024/06/25/ai-mapping-suffering/ 12. ​Schukraft J. Differences in the Intensity of Valenced Experience across Species. Rethink Priorities; 2020. Available: https://forum.effectivealtruism.org/posts/H7KMqMtqNifGYMDft/differences-in-the-intensit y-of-valenced-experience-across 13. ​Visak T. Capacity for Welfare Across Species. Oxford University Press; 2023. 39 14. ​Alonso WJ, Schuck-Paim C. Do primitive sentient organisms feel extreme pain? disentangling intensity range and resolution. EA Forum. 2025. Available: https://scholar.google.com/citations?view_op=view_citation&hl=en&citation_for_view=smt CsdwAAAAJ:hZ5_QnqxF7AC 40