Heather Browning

There are many decision contexts in which we require accurate information on animal welfare, in ethics, management, and policy. Unfortunately, many of the methods currently used for estimating animal welfare in these contexts are subjective and unreliable, and thus unlikely to be accurate. In this paper, I look at how we might apply principled methods from animal welfare science to arrive at more accurate scores, which will then help us in making the best decisions for animals. I construct and apply a framework of desiderata for welfare measures, to assess the best of the currently available methods and argue that a combined use of both a whole-animal measure and a combination measurement framework for assessing welfare will give us the most accurate answers to guide our action.

Synthetic meat made from animal cells will transform how we eat. It will reduce suffering by eliminating the need to raise and slaughter animals. But it will also have big public health benefits if it becomes widely consumed. In this paper, we discuss how “clean meat” can reduce the risks associated with intensive animal farming, including antibiotic resistance, environmental pollution, and zoonotic viral diseases like influenza and coronavirus. Since the most common objection to clean meat is that some people find it “disgusting” or “unnatural,” we explore the psychology of disgust to find possible counter-measures. We argue that the public health benefits of clean meat give us strong moral reasons to promote its development and consumption in a way that the public is likely to support. We end by depicting the change from farmed animals to clean meat as a collective action problem and suggest that social norms rather than coercive laws should be employed to solve the problem.

One of the most challenging questions surrounding subjective animal welfare is whether these states are measurable: that is, is subjective welfare an appropriately quantifiable target for scientific enquiry and ethical and deliberative calculation? The availability of several different types of measurement scale raises important questions regarding whether subjective experience has the right properties to be meaningfully represented on the types of scale required for different applications. This methodological question has so far received scant attention in the animal welfare literature. In this paper, I address this omission by examining the types of measurement scale we can reasonably expect to apply to animal welfare measurements, and which we will actually need for our applications. I argue that our different applications will require variously ordinal, interval, and ratio scales, and that we have sufficient reason to believe that subjective welfare is a target with the appropriate characteristics to justify the practice of representing it using each of these types of scales.

Measurement of subjective animal welfare creates a special problem in validating the measurement indicators used. Validation is required to ensure indicators are measuring the intended target state, and not some other object. While indicators can usually be validated through looking for correlation between target and indicator under controlled manipulations, this is not possible when the target state is not directly accessible. In this paper, I outline a four-step approach using the concept of robustness, that can help with validating indicators of subjective animal welfare.