European Journal for Philosophy of Science
https://doi.org/10.1007/s13194-020-00322-9
(2021) 11:9
PAPER IN PHILOSOPHY OF SCIENCE IN PRACTICE
Open Access
Perspectival pluralism for animal welfare
Walter Veit 1
& Heather
Browning 2,3
Received: 10 October 2019 / Accepted: 22 September 2020/
# The Author(s) 2020
Abstract
Animal welfare has a long history of disregard. While in recent decades the study of animal
welfare has become a scientific discipline of its own, the difficulty of measuring animal
welfare can still be vastly underestimated. There are three primary theories, or perspectives,
on animal welfare - biological functioning, natural living and affective state. These come
with their own diverse methods of measurement, each providing a limited perspective on an
aspect of welfare. This paper describes a perspectival pluralist account of animal welfare, in
which all three theoretical perspectives and their multiple measures are necessary to
understand this complex phenomenon and provide a full picture of animal welfare. This
in turn will offer us a better understanding of perspectivism and pluralism itself.
Keywords Perspectivism . Models . Pluralism . Methodological anarchism . Animal
welfare
1 Introduction
Animal welfare has a long history of disregard. In early Western philosophy, Aristotle
argued that animals lacked moral status as they lacked the capacity to reason, and this
tradition continued through to the Cartesian perspective of animals as automata that lacked
mental states (Regan and Singer 1976). This view has now been largely overturned in favour
of one that recognises animals as sentient creatures with moral value, thanks to earlier work
This article belongs to the Topical Collection: Perspectivism in science: metaphysical and epistemological reflections
Guest Editors: Michela Massimi
* Walter Veit
wrwveit@gmail.com
* Heather Browning
DrHeatherBrowning@gmail.com
1
School of History and Philosophy of Science, University of Sydney, Sydney, Australia
2
Centre for Philosophy of Natural and Social Science, London School of Economics and Political
Science, London, UK
3
Department of Philosophy, The University of Sydney, Sydney, Australia
9
Page 2 of 14
European Journal for Philosophy of Science
(2021) 11:9
by Jeremy Bentham (1879) and more recently through attention gained by Peter Singer
(1975) and Tom Regan (1983). Indeed, during recent decades, animal welfare has also
become a scientific discipline of its own.1 The difficulty of measuring animal welfare,
however, can still be vastly underestimated. In this paper, we will argue for the use of
perspectival pluralism for animal welfare and show that animal welfare provides a useful and
novel case to explore the application of this approach for complex phenomena.
The paper is structured as follows: in Section 2, we explicate the philosophical
doctrine of perspectivism and its links to pluralism. In Section 3 we describe the
different perspectives on animal welfare and in Section 4 outline the current measurement methods. Section 5 offers a perspectival pluralist approach to integrate these
methods and provide a better scientific understanding of animal welfare. Lastly,
Section 6 concludes the discussion and points to some further avenues for future
research on both perspectivism and animal welfare.
2 Perspectivism and pluralism
Perspectivism2 has gained increasing prominence within the philosophy of science community as an alternative and “refreshingly new” (Massimi 2012, p. 25) competitor in the
rather stale debate between scientific realists and anti-realists. Whereas realists take scientific
measurement to reveal objective facts and truths about the underlying structure of the world,
and anti-realists deny this; perspectivists take a middle ground in which the facts and truths
revealed are dependent on some specific perspective. Despite the popularity of the view,
there is no simple or straightforward definition of perspectivism that would capture the
views of all of its proponents. Indeed, perspectivists can be found within both the instrumentalist and realist camps of science. Nevertheless, there is a conciliatory element to the
various accounts that fits the label ‘perspectivism’.
While the roots of perspectivism go back to major philosophical figures such as
Nietzsche, Leibniz, Kant, and Wittgenstein (see Massimi 2012; Teller 2020), it was
Ronald N. Giere (2006a) who introduced this perspective into the philosophy of
science.3 The following quote aptly illustrates Giere’s motivation:
We simply cannot transcend our human perspective, however much some may
aspire to a God’s eye view of the universe. Of course, no one denies that doing
science is a human activity. What needs to be shown in detail is how the actual
practice of science limits the claims scientists can legitimately make about the
universe. (Giere 2006a, p. 15)
Scientific investigation is always relative to some perspective. Scientists have different
perspectives, arising from their background theories and the capabilities of their
1
See Browning (2020b) for an overview.
Or perspectivalism - both have both been used interchangeably in the literature (see Massimi and McCoy
2020). As nothing hangs on the choice of usage between the two, we chose the former merely for the sake of
brevity.
3
Bas van Fraasen also contributed substantially to the rise of perspectivism, though he did not use the term
and, contrary to Giere, argued for an anti-realist picture of science (Van Fraassen 2008).
2
European Journal for Philosophy of Science
(2021) 11:9
Page 3 of 14
9
measurement instruments, each of which can reveal only a partial view of the objects
under investigation.
This leads naturally to the endorsement of a pluralist view (Giere 2006b). In this,
perspectivism and pragmatism share a variety of features that illuminate the benefits of
taking multiple perspectives on a phenomenon (see also Massimi and McCoy 2020).
Unlike the historically received view in the philosophy of science, i.e. the Nagelian “view
from nowhere” (Nagel 1989), in which a completely objective and “detached” perspective
is preferred – perspectivists and pragmatists deny that such an entirely neutral or objective
foundation exists from which science could proceed.4 Instead, we require multiple
perspectives if we are to gather an approximately complete picture. Given that no single
perspective can offer a uniquely correct and complete picture of the world, use of multiple
perspectives together can thus create a far richer understanding.5 Contributions from
feminist philosophy of science6 have similarly undermined the popularity of ‘Nagelian
terminology’ and talk of objectivity, yielding the subject to historians of science (Daston
and Galison 1992, 2007) and the rapidly growing ‘values in science’ literature (see for
instance Douglas 2009). Perspectivism, while sharing much with these two traditions, can
nevertheless be understood as a distinctive movement.
Perspectivism in science can arise in two ways - in observation (measurement) and in
theory (Giere 2006a). Measurement is perspectival in that measurement instruments and
human observation are necessarily limited and occur from a particular viewpoint - no
instrument can measure everything. So too is the creation of theories perspectival: “in
creating theories ... scientists create perspectives within which to conceive of aspects of the
world” (Giere 2006a, p. 59). Theories are also partial, and each will rule some things out.
Thus the way we theorise may limit the way we understand phenomena. A striking
example of the strength of theoretical perspectivism can be seen in biological research on
the major transitions in individuality. The traditional picture of the major transition
towards multicellular organisms associated ‘cheating cells’ occurring in a group arrangement (i.e. in a gametheoretic sense) as an evil that somehow needs to be ‘eradicated’ to
enable a transition towards a higher-level Darwinian individual. However, a number of
theoretical biologists suggested taking a ‘different perspective’ that allows a reinterpretation of ‘cheating’ cells within multicellular arrangements instead as proto
germ-cells playing the role of ‘saviors’ for group-level entities and ‘scaffolds’ for the
evolution of multicellularity.7 Here, it was perspectival pluralism that enabled a new
explanatory strategy that was not even conceivable in the traditional paradigm.
We are thus aligning ourselves with Massimi’s more deflationary vision of
perspectivism as a view of how scientific knowledge about nature is obtained, rather
than what scientific knowledge is (Massimi 2012). This shift in how perspectivism is
understood softens the boundaries of the position and moves it much closer to other
‘pluralist’ thinkers in the literature such as Sandra Mitchell (2002, 2003, 2009, 2020),
Helen Longino (2012, 2013, 2016, 2019), and philosophers of science more generally
4
This tension points to an interesting relationship here between what have been dubbed ‘existentialist’ and
‘scientistic’ philosophies that insist on the meaninglessness and absurdity of the ‘objective’ stance (from
nowhere) for the perspective of human beings (see Camus 1955; Nagel 1971; Rosenberg 2011; Veit 2018).
5
A similar idea is present in Railton’s (1978, 1981) concept of an ‘ideal explanatory text’ containing all the
information relevant for the explanandum at hand.
6
An excellent overview of the development of this literature is provided in Longino (2017, 1987).
7
See Rainey and Kerr (2010); Hammerschmidt et al. (2014); Veit (2019a).
9
Page 4 of 14
European Journal for Philosophy of Science
(2021) 11:9
associated with what have been dubbed the Stanford School and Minnesota School
respectively.8 A trend in the work of Nancy Cartwright and her ‘followers’ since “How
the laws of physics lie” (Cartwright 1983) has been to emphasize the need for models
due to the chaotic patchwork that is nature. It is thus not surprising that her work has
similarly been placed within a perspectival pluralist framework even if she herself
didn’t make use of ‘perspectivist’ language (Pearce 2013; Teller 2020; Veit 2020).9
Different methods and models offer different perspectives and ways of gaining
knowledge. One of the most radical forms such a pluralist perspectivism can take is
the “strong model pluralism” articulated in Veit (2019b): “for almost any aspect x of
phenomenon y, scientists require multiple models to achieve scientific goal z” (pp. 92–
93). This thesis is intended to explain the usage of multiple highly idealized and
abstract models that seemingly contradict each other. In the scientific study of morality,
for instance, the use of such simple models is common, and one needs to appreciate the
perspectival nature of the contributions by this large set of models, as one that only
jointly illuminates a phenomenon as complex as human morality (Veit 2019c). In this
paper, we merely want to suggest that animal welfare is a phenomenon just as complex
and thus similarly requires a radical perspectival pluralism. After all, it is only rarely if
ever the case that much can be learned by a single method, experiment, or measurement
- science requires pluralism and diversity even on the lowest scale. Interpreted literally,
such arguments evoke the anarchist spirit of Feyerabend (1975) and this is by no means
unintentional. As Veit et al. (2020) argues, a proper understanding of the nature of
models in science would force us to accept a sort of Feyerabendian “model anarchism”.
At the lowest individual level it thus becomes hard to resist the radically relativist
conclusion that anything goes.
This human vantage point thus naturally raises a number of familiar philosophical
issues such as the problems of measurement, realism, pluralism, modelling, and
representation. Here, we will demonstrate how the study of animal welfare as a
scientific phenomenon provides an attractive case to illustrate the strength a pluralist
perspectivism has to offer. Animal welfare is a complex concept, of which there are
multiple theoretical perspectives and associated different measurement methods, each
with differing strengths and weaknesses and which shed light on different aspects of the
phenomenon of welfare. We will demonstrate how, taken together, these jointly offer a
much more illuminating picture of the scientific phenomenon of interest than any
would if taken individually. As we shall show, this diversity is to be embraced, rather
than avoided.
3 Animal welfare perspectives
Metrics for the measurement of animal welfare play a range of diverse roles throughout
science and policy-making (e.g. Browning 2018a, 2018b; Browning and Maple 2019).
Measurement of animal welfare relies on a particular underlying conceptual understanding of welfare and what it is composed of (Browning 2020a), which we will
examine in more detail in the next section. As we have discussed, theorising is itself
8
9
See Kellert et al. (2006) for a landmark volume on scientific pluralism.
This is particularly noticeable in her latest work (see Cartwright 2019).
European Journal for Philosophy of Science
(2021) 11:9
Page 5 of 14
9
perspectival, and we can thus take different theories to represent different perspectives
on a concept. There are several different such theories, or perspectives, on animal
welfare (Duncan and Fraser 1997). Welfare is a ‘thick’ concept, one which requires an
evaluative, as well as a scientific understanding (Robbins et al. 2018), and thus a
welfare concept must also capture normative concerns. The three primary views are
what Green and Mellor (2011) describe as the ‘three orientations’: biological function,
natural living, and affective state. These three theories have been discussed at length in
the literature, analysing their various strengths and weaknesses (e.g. Appleby and
Sandøe 2002). Each of these concerns different sources of value, as well as differing
theoretical commitments. In this paper, we argue that all three different perspectives are
necessary to understand a phenomenon as complex and diverse as animal welfare, both
in terms of providing a broader conceptual understanding, and in supporting a range of
different measures.
The biological function perspective focuses on the physical wellbeing of an animal.
This includes its physical health, growth rate and reproduction. In particular, this
approach has been characterised by a focus on stress and its resultant physiological
effects (Duncan and Fraser 1997). This approach was popular in the early days of
animal welfare science, through the 1980s and 1990s (e.g. Broom 1988). This was
largely due to a behaviourist preference for objective measures, and a reluctance to
discuss or engage with the emotions or mental states of animals within a scientific
context. It is often based in an underlying commitment to evolutionary considerations,
that take the biological functioning and fitness of an organism to be centrally determinant of its welfare (Barnard and Hurst 1996). In this, it has some connections to the
natural living perspective. This perspective typically links most closely with a humancentred ethics, in which the welfare of animals is important to ensure high levels of
production and success within animal industries, particularly agricultural. Here, the
biological functioning of animals matters to serve these economic ends, whereas their
feelings are of little concern except insofar as they may cause physical effects, such as
stress.
This is the major drawback to this perspective: that in this way physical functioning
misses what are typically taken to be important aspects of welfare. An animal can be
entirely fit and healthy, but still feel bored, lonely and frustrated, and thus have poor
welfare. As the science progressed and acknowledged the importance of psychological
wellbeing, this approach - at least as taken alone - fell out of favour, and it is now
almost always used in combination with others. Although physical functioning is not
sufficient for describing welfare, it is still highly important. Physical health and fitness
will have large impacts on animal welfare; and an animal that is sick or injured will
have compromised welfare.
The natural living perspective focuses on the wild state of animals and their ability to
function according to how they have been shaped by evolution. This approach recognises the ‘telos’ of animals, the “physical, behavioural, and psychological interests that
have been programmed into them in the course of their evolutionary development”
(Rollin 2006, pp. 300–01). In particular, as opposed to the focus on physical functioning found in the biological functioning perspective, it is often used to emphasise the
importance for animals of expressing their natural behaviours. This perspective is
aligned with an animal rights ethics, that centres the animals themselves as sources
of value; in particular their dignity and flourishing, which are taken to be closely linked
9
Page 6 of 14
European Journal for Philosophy of Science
(2021) 11:9
with natural living. Here, the ability to perform those set of behaviours that the species
has evolved for is considered to be of the highest value in creating a flourishing animal
(Nussbaum 2009).
The natural living perspective has been criticized for its limitations, as many aspects
of the ‘natural’ lives of animals (i.e. those experienced in the wild) can be detrimental to
welfare (e.g. predation, disease) (Mellor 2015). An animal can be living a perfectly
natural life, but suffer immensely from these effects. It is therefore typically used
instrumentally, in identifying living conditions or behaviours that may be beneficial
to welfare as understood through one of the other approaches (Browning 2019). In the
absence of other confounding factors, natural living is often a good guide to those
conditions and behaviours that will benefit welfare (Špinka 2006). There is thus an
underlying rationale for this perspective that should not be entirely discarded but
instead incorporated into the understanding and measurement of welfare.10
The affective state perspective takes welfare to consist in the mental states, or
affects, of animals and is also often known as the ‘feelings-based’ approach (Duncan
and Fraser 1997). Here, it is the positive and negative experiences animals undergo and their associated affects - that determine their welfare. Positive feelings (such as
comfort or curiosity) increase welfare, while negative feelings (such as hunger or pain)
decrease welfare. The welfare of an animal is then simply a function of the number of
positive and negative experiences over a lifetime. Only those conditions that influence
the subjectively experienced mental states of animals will be counted as welfare
impacts. This perspective is typically used within utilitarian ethics, which take as
morally important the amount of pleasure or suffering experienced by individuals including animals (Singer 1975). Under almost all conceptions, the feelings of animals
- their pleasure and suffering - is central to considerations of welfare. As such, the
affective state perspective is now commonly accepted as necessary for welfare. However, it is often considered insufficient. An animal may experience nothing but
happiness lying around eating chocolate, but the resulting health compromise will lead
to poor welfare.
Many authors take the three perspectives together and endorse a multicomponent or
‘tripartite’ framework (e.g. Fraser 1999; Jones 2013; Maple and Perdue 2013). For
example, Fraser argues “that animals should feel well by being free from prolonged or
intense fear, pain and other unpleasant states, and by experiencing normal pleasures;
that animals should function well in the sense of satisfactory health, growth and normal
behavioral and physiological functioning; and that animals should lead natural lives
through the development and use of their natural adaptations” (Fraser 1999, p. 178,
italics in original). Here, it seems that the authors are taking these as three different
components within a multifactorial theory, rather than genuinely distinct perspectives.
However, we think that the differences between these theories are too deep for the
possibility of easily combining them in this way. As we have discussed, each of these
theories contains different values and background assumptions that resist integration, as
well as the different measurement methods we will introduce in the next section. Use of
all three perspectives is judged to be crucial for a complete conceptual understanding
10
As Dennett illustrates, this sort of adaptive reasoning or “reverse engineering” is often useful, both in
everyday and scientific reasoning, and should thus not be ignored when we are trying to understand animal
welfare (see Dennett 1995, 1998, 2017; Veit et al. 2020).
European Journal for Philosophy of Science
(2021) 11:9
Page 7 of 14
9
and for the measurement of welfare. Particularly, this diversity of perspectives may
better reflect the intuitive judgements that accompany the folk concept of welfare
(Robbins et al. 2018).
As discussed above, all the perspectives contain something of importance to animal
welfare, capturing different sources of value as well as conditions that will impact
welfare, and any of them taken alone risk missing the whole picture. Welfare is
complex and thus no single theory will provide sufficient information about all its
parts. There are also multiple, complementary methods of measurement of animal
welfare, each of which is based in different welfare theories and necessarily captures
a different perspective, and as we will now show, should also be used together to best
capture a complete picture of animal welfare.
4 Measuring animal welfare
As discussed in Section 2, perspectivism is present in both theory and measurement.
Different theories and measurement techniques each come from a limited perspective
and can not on their own reveal all there is to know about complex phenomena. This is
also the case for animal welfare. As well as the theoretical perspectives described
above, there are different ways of measuring welfare that operate with different
methods and background assumptions. These can be located within the three theoretical
perspectives and, as we will show, when combined can give a far richer picture of
animal welfare than any single measurement taken alone.
There are numerous measures for animal welfare, which can be grouped as physical,
behavioural and environmental. Each of these categories contain a number of different
measures, which reflect different processes within the animals or external environmental conditions. Physical and behavioural indicators are measures taken of various
properties of the animals themselves, and are also collectively known as ‘animal-based’
indicators. These indicators stand causally ‘downstream’ from welfare - they are the
effects we observe resulting from changes in welfare. By contrast, environmental
indicators are measures of the conditions in which the animals live. These stand
causally ‘upstream’ from welfare - they are the causes of changes in welfare
(Browning 2020b). None of these indicators are intended to measure welfare in its
entirety, but rather to shed light on some small part of an animal’s condition. This
reflects the perspectivalism inherent in measurement - these are necessarily limited and
can only provide a partial view of the phenomenon of welfare. For this reason, taking
different measurements together will be essential for a complete picture of animal
welfare. Indeed, as we will show, many current animal welfare measurement frameworks do just this, in an attempt to fully understand and describe welfare.
Measures of biological functioning are primarily physical measures. These measures
rely on background assumptions about the effects of health and functioning on welfare,
based in the theory within the biological functioning perspective; particularly the
degree to which welfare is compromised by the malfunctioning of different bodily
systems. They include a variety of health data, such as blood tests, organ function tests,
presence of injury or lameness etc. Physiological indicators can also tell us about the
level of stress an animal is experiencing. The most commonly used of these is
measuring cortisol, or its byproducts, in the blood, saliva, or faeces. Cortisol is a
9
Page 8 of 14
European Journal for Philosophy of Science
(2021) 11:9
hormone associated with the stress response, and so elevated levels can indicate the
presence of stress and possible corresponding reduction in welfare. Vital signs, such as
heart rate or body temperature, can similarly indicate the presence of stress, as well as
disease or injury. Some behavioural measures can also be used within this perspective for example, movement and activity level can indicate physical health. Sick and injured
animals can often be identified by changes in behaviour such as withdrawal from social
companions and loss of interest in eating, drinking or other preferred activities.
Measures of natural living are primarily behavioural. The relevant behavioural
measures are ethograms, and presence or absence of abnormal behaviours. Ethograms
are used to look at the behavioural repertoire of a captive animal to see how much time
it spends in different behaviours (activity budget) and the range of behaviours it
performs. Comparing these to those of wild relatives can provide information on how
closely the life of the captive animal matches that of its ‘natural’ state.11 This relies on
background assumptions about the appropriate level of similarity between wild and
captive animals. Preference and motivation tests can additionally be used to show
which behaviours of this type the animal most values (Dawkins 1990). Additionally,
the presence or absence of abnormal behaviours are indicative of natural functioning.
Stereotypies are repetitive behaviours such as pacing, swaying, or self-plucking and
their presence typically assumed to signal boredom or frustration, where an animal is
unable to perform a highly motivated behaviour and instead redirects its energies into
the observed unnatural stereotypy (Duncan and Fraser 1997).
Within the affective state perspective, the primary measures are also behavioural. In
particular, there are two ‘whole animal’ measures that aim to assess the overall subjective
experience or mood of an animal – Qualitative Behavioural Assessment (QBA) and
cognitive bias testing. In QBA, experienced observers (such as animal keepers or scientists) make assessments about the overall welfare status of an animal based on what they
see of its behaviour, demeanour, body language, vocalisations etc. (Wemelsfelder et al.
2001). This method shows high reliability across observers (Wemelsfelder et al. 2001) and
has been validated through correlation with other relevant physiological and behavioural
indicators (Wemelsfelder 2007). Cognitive bias testing similarly aims to measure the
overall ‘mood’ of an animal; representative of the cumulative affective welfare state of an
animal, a function of the combined positive and negative experiences (Mendl et al. 2010).
Mood will affect cognitive processes, creating measurable cognitive biases that can be
used to gain information about welfare (Boissy and Lee 2014). Another behavioural
indicator of affective state is preference testing. Preference tests give animals choices
between different alternatives to see which they will choose, and how hard they will work
for it, giving information on the strength of their preferences for different conditions
(Dawkins 1983). Background theory and assumptions play an especially strong role
within measures of affective state, as the links between observed behaviour and internal
feelings cannot be determined empirically but only ever supported.
These animal-based measures give us valuable information about the welfare state of an
animal. However, what they don’t tell us about is which conditions are causing welfare
change. For this, we use environmental measures. Environmental indicators are measures
taken of the environmental conditions in which animals live. They can include information
11
Though caution must be taken in interpreting these results (see e.g. Veasey et al.
1996a, b; Browning 2019)
European Journal for Philosophy of Science
(2021) 11:9
Page 9 of 14
9
about food type and availability, temperature, air flow, light levels, resting places,
stockmanship and provision of behavioural opportunities (e.g. dirt floors for chickens to
dustbathe). These indicators tell us about the causes of welfare changes for animals and can
be used within any of the animal welfare perspectives. They link to the background theories
in each of the perspectives, where the presence of conditions which promote physical health,
natural behaviour and positive experience will be considered to be positive indicators of
welfare, while those which may cause disease or injury, behavioural restriction or negative
affects will be considered to be negative indicators of welfare. Environmental measures can
also be used as proxies for other animal welfare measures, where they are found to correlate
well. For example, if type of flooring correlates with prevalence of lameness, then we could
simply observe flooring type as a proxy for this health measure.
Indicators of animal welfare are strongly perspectival. All of the proxy indicators
described above give us some limited information about an aspect of animal welfare whether an animal is healthy, whether it has opportunities for some range of natural
behaviours, whether it is experiencing positive or negative affective states. Any single
measure on its own will not provide much information about welfare - like a single torch, it
will only light up one small part of the whole. While they may be useful in specific
contexts - such as answering a question about adequate nutrition, or whether an animal is
feeling fearful - they will fall short for most applications in which we want to judge the
entire welfare state of an animal, such as when we are comparing the overall quality of
different husbandry systems. For these, we need an integration of multiple perspectives.
5 Integrating perspectives on animal welfare
All the measures described in the previous section are taken from different perspectives.
Any single proxy measure will only give a small piece of information from a limited
perspective and use of a plurality of methods of measurement is thus our best approach
to measuring welfare. The measurement types all have different benefits and drawbacks. For example, behavioural measures such as QBA and cognitive bias testing can
be vulnerable to bias in observation and measurement, due to the partially subjective
nature of the assessment (Beausoleil and Mellor 2011). Indeed, perspectivists have
pointed out that this type of subjective bias is a problem inherent within science,
however, pluralism with regard to different perspectives is likely to minimize potential
biases introduced through researchers. Other physical measures will be vulnerable to
other kinds of bias in interpretation, for example in terms of how strongly the measured
indicators are taken to impact welfare. Using multiple measures alongside one another
will allow us to gain the benefits of each method, while offsetting their drawbacks.
Different types of welfare measure strengthen one another and provide complementary
perspectives. They also throw light on different aspects of animal welfare and any one
alone will not provide a complete picture. For example, if we failed to include an
indicator for social behaviour in a highly social animal held in a solitary environment,
we might conclude that welfare was good, even though an important component of
natural behaviour is missing. For these reasons, they are strongest when used in
combination through a pluralist approach. It is for these reasons that their combined
use is not only beneficial but necessary (see also Van Fraassen 2008 and Wolff 2020 on
the relation between perspectivism and measurement more generally).
9
Page 10 of 14
European Journal for Philosophy of Science
(2021) 11:9
There are a number of assessment frameworks which aim to integrate a range of
proxy measures, bringing together different of perspectives in a version of a perspectival pluralist approach. These frameworks include the Five Domains (Mellor and
Beausoleil 2015), Welfare Quality (Botreau et al. 2007), and SOWEL and related
models (Bracke et al. 2002). They recognise that no single proxy measure will be
sufficient for determining welfare and so use a variety of different indicators,
representing different perspectives that tell about some limited aspect of welfare. These
are typically grouped into different ‘principles’ (Botreau et al. 2009) or ‘domains’
(Mellor and Beausoleil 2015) which are roughly the same across the different frameworks - feeding, housing, health and behaviour, based on the original ‘Five Freedoms’
framework for animal welfare (FAWC 1979). A number of specific subcriteria are
determined for each of these: for example the ‘nutrition’ domain would contain
components for amount of food, amount of water, timing of feeding etc. These
subcriteria are then measured using the types of proxy indicators described above.
The different measures are brought together using various aggregation procedures to
create a final overall welfare score.
Although proxy measures brought together in these frameworks, can provide a lot of
detail about animal welfare, care must be taken with selection and aggregation procedures. These will depend strongly on the underlying perspective taken. Not all aspects
of welfare will have the same impact, and the level of impact we take them to have will
depend on the particular perspective - biological functioning will weight illness and
injury highly, while affective state will prioritise types of psychological suffering.
Currently, the weighting procedures are often based on expert assessment, which
makes them highly opaque and unreliable (Spoolder et al. 2003). The SOWEL-type
models do better in attempting to take weightings from available literature (Bracke et al.
2002), but these are all still firmly grounded in the perspectives of the individual
scientists making the judgements, and related background assumptions regarding, for
example, the relationship between preferences and welfare.
Another related concern regarding the risks in bringing together multiple perspectives and measurements for a pluralist study of animal welfare is that the measures and
recommendations arising from each may conflict. For example, many zoos used to
have concrete and tiled cages, which allowed for maximising welfare from a physical
functioning perspective, through thorough cleaning and disinfecting. However, the lack
of environmental complexity and mental stimulation detracted from welfare from both
the natural living and affective state perspectives. Similarly, allowing an animal to
choose its own preferred food would be a benefit from an affective state perspective in
creating positive feelings of taste pleasure and satiety, but a drawback from a physical
functioning perspective due to weight gain and malnutrition. It is important, when
adopting a plurality of perspectives, to ensure that there is a way of adjudicating
between their competing demands and setting weightings between the different components. However, there is no ‘objective’ or ‘perspective-neutral’ viewpoint from
which to assess the weightings of various inputs.
Regardless, these concerns do not make integration an unachievable task. We can
still proceed even if we do not consider there to be any single privileged way of
combining the perspectives into a single model. Instead, there may be multiple
methods, each themselves based on the different background assumptions, normative
commitments, and individual preferences that arise from each perspective. The problem
European Journal for Philosophy of Science
(2021) 11:9
Page 11 of 14
9
of determining weightings may not be an empirical one, as there might be no privileged
‘correct’ set of weightings. Instead, we look for one which best suits our purposes. In
making animal welfare assessments, these purposes are typically for making decisions
about where best to use our resources to maximise welfare. Here, we might consider
using robustness reasoning (Wimsatt 2007). This would entail comparing the decisions
recommended by different models, and preferentially selecting those recommended by
many or most models. Or where trying to determine whether a particular intervention is
a good use of resources, we could then observe whether it gives a predicted welfare
increase across the different models. In practice, often the recommendations from the
different welfare perspectives align, and so this should not be excessively demanding.
Perspectival pluralism for animal welfare allows us to integrate multiple perspectives, both theoretical and practical. We have described three primary theoretical
perspectives on animal welfare - the biological function, the natural living and the
affective state perspectives. Any of these perspectives on their own are incomplete, and
a complete understanding of animal welfare requires use of the plurality of these
together. Their combined use, along with multiple methods of measurement gives us
the best picture of the phenomenon we are studying.
6 Conclusion
In this paper, we have argued for the use of different theories and methods for
conceptualising and measuring animal welfare and that the existence of such widely
varying methods is a feature not a bug. As perspectivists, such as Giere (2006a), Van
Fraassen (2008), Wimsatt (2007), Mitchell (2020), Massimi (2012), Teller (2020),
Chang (2012), and Veit (2019b, 2020) have argued, multiple scientific perspectives
are a source of strength rather than a weakness. Complex phenomena such as welfare
may very well require the use of different tools and methods. This does not have to lead
to scientific anti-realism about the phenomenon of welfare, but rather points to a more
sensible and pragmatic account of scientific realism that takes the complexity of
phenomena and the limits of the human mind and our scientific tools seriously. As
Massimi and McCoy argue:
Pluralism is, first and foremost, a powerful resource in the hands of
perspectivists because it shows how they can accommodate and strive to integrate a plurality of explanations for the same phenomena in some areas.
(Massimi and McCoy 2020, p. 3)
Perspectivism raises not only philosophical puzzles when applied to specific scientific
problems such as the measurement of welfare, but also for metadebates in the philosophy of science literature more generally. Our aim here was to illustrate the benefits of
a perspectivist pluralist approach through the case of animal welfare science. Animal
welfare is real and measurable, and although incredibly complex, no less so than its
human counterpart. More work needs to be undertaken in order to fully understand the
importance of diverse perspectives and methods, but we are confident that our analysis
of animal welfare allows us not only to better understand animal welfare itself, but also
illuminates several of the more general philosophical puzzles raised by perspectivism.
9
Page 12 of 14
European Journal for Philosophy of Science
(2021) 11:9
Importantly, however, we hope that the foregoing analysis has demonstrated a way to
partially escape the limited human perspective via the use of a plurality of diverse
methods to explore a complex phenomenon.
Funding HB’s research is part of a project that has received funding from the European Research Council
(ERC) under the European Union’s Horizon 2020 research and innovation programme, Grant Number
851145; WV’s research funded through Paul Griffith’s Australian Laureate Fellowship project “A Philosophy
of Medicine for the 21st Century” [Ref: FL170100160].
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and
indicate if changes were made. The images or other third party material in this article are included in the
article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not
included in the article's Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
References
Appleby, M. C., & Sandøe, P. (2002). Philosophical debate on the nature of well-being: Implications for
animal welfare. Animal Welfare, 11(3), 283–294.
Barnard, C. J., & Hurst, J. L. (1996). Welfare by design: The natural selection of welfare criteria. Animal
Welfare, 5(4), 405–433.
Beausoleil, N.J. and Mellor, D.J. (2011). Complementary roles for Systematic Analytical Evaluation and
qualitative Whole Animal Profiling in welfare assessment for Three Rs applications. Proceedings of the
8th World Congress on Alternatives and Animal Use in the Life Sciences, Montreal, Canada, 21–25.
Bentham, J. (1879). An introduction to the principles of morals and legislation. London: T. Payne & Son.
Boissy, A., & Lee, C. (2014, April). How assessing relationships between emotions and cognition can
improve farm animal welfare. Revue Scientifique et Technique de l’OIE, 33(1), 103–110.
Botreau, R., Veissier, I., Butterworth, A., Bracke, M. B. M., & Keeling, L. J. (2007). Definition of criteria for
overall assessment of animal welfare. Ani-mal welfare-potters bar then wheathampstead, 16(2), 225.
Botreau, R., Veissier, I., & Perny, P. (2009). Overall assessment of animal welfare: Strategy adopted in
welfare quality R. Animal Welfare, 18(4), 363–370.
Bracke, M. B. M., Spruijt, B. M., Metz, J. H. M., & Schouten, W. G. P. (2002, July). Decision support system
for overall welfare assessment in pregnant sows a: Model structure and weighting procedure. Journal of
Animal Science, 80(7), 1819–1834.
Broom, D. M. (1988). Needs, freedoms and the assessment of welfare. Applied Animal Behaviour Science,
19(3–4), 384–386.
Browning, H. (2018a). No room at the zoo: Management euthanasia and animal welfare. Journal of
Agricultural and Environmental Ethics 31(4), 483–498. https://doi.org/10.1007/s10806-018-9755-2.
Browning, H. (2018b). Won’t somebody please think of the mammoths? De-extinction and animal welfare. Journal
of Agricultural and Environmental Ethics 31(6), 785–803. https://doi.org/10.1007/s10806-018-9755-2.
Browning, H. (2019). The natural behavior debate: Two conceptions of animal welfare. Journal of Applied
Animal Welfare Science, 1–13. https://doi.org/10.1080/10888705.2019.1672552.
Browning, H. (2020a). Assessing measures of animal welfare. Preprint. http://philsci-archive.pitt.edu/17144/.
Browning, H. (2020b). If I Could Talk to the Animals: Measuring Subjective Animal Welfare. Ph. D. Thesis,
Australian National University. https://doi.org/10.25911/5f1572fb1b5be.
Browning, H. and Maple, T.L. (2019). Developing a Metric of Usable Space for Zoo Exhibits. Frontiers in
Psychology 10, 791. 10. 3389/fpsyg.2019.00791.
Camus, A. (1955). The myth of Sisyphus: And other essays. Random House digital, Inc. translated from the
French original (1942) by Justin O’Brien.
Cartwright, N. (1983). How the Laws of physics lie. Oxford: Oxford University Press.
European Journal for Philosophy of Science
(2021) 11:9
Page 13 of 14
9
Cartwright, N. (2019). Nature, the artful modeler: Lectures on laws, science, how nature arranges the world
and how we can arrange it better. Chicago: Open Court.
Chang, H. (2012). Is water H2O?: Evidence, realism and pluralism. Springer.
Daston, L., & Galison, P. (1992). The image of objectivity. Representations, 40, 81–128.
Daston, L. and Galison, P. (2007). Objectivity. Zone Books.
Dawkins, M. S. (1983). Battery hens name their price: Consumer demand theory and the measurement of
ethological ‘needs’. Animal Behaviour, 31(4), 1195–1205.
Dawkins, M. S. (1990). From an animal’s point of view: Motivation, fitness, and animal welfare. Behavioural
and Brain Sciences, 13(1), 1–9.
Dennett, D. C. (1995). Cognitive science as reverse engineering several meanings of “Top-down” and “Bottomup”. In Studies in Logic and the Foundations of Mathematics, Volume 134, pp. 679–689. Elsevier.
Dennett, D. C. (1998). Brainchildren: Essays on designing minds. MIT Press.
Dennett, D. C. (2017). From bacteria to Bach and back: The evolution of minds. WW Norton & Company.
Douglas, H. (2009). Science, policy, and the value-free ideal. University of Pittsburgh Press.
Duncan, I. J., & Fraser, D. (1997). Understanding animal welfare. In M. Appleby & B. O. Hughes (Eds.),
Animal welfare (pp. 19–32). New York: CAB International.
Farm Animal Welfare Council (FAWC). (1979). Farm animal welfare council press Statement. Retrieved from
http://webarchive.nationalarchives.gov.uk/20121010012427/http://www.fawc.org.uk/freedoms.htm.
Feyerabend, P. (1975). Against method. Verso.
Fraser, D. (1999). Animal ethics and animal welfare science: Bridging the two cultures. Applied Animal
Behaviour Science, 65(3), 171–189.
Giere, R. (2006a). Scientific Perspectivism. Chicago: University of Chicago Press.
Giere, R. N. (2006b). Perspectival pluralism. In S. H. Kellert, H. E. Longino, and C. K. Waters (Eds.),
Scientific Pluralism, chapter 2, pp. 26–41. Minneapolis: University of Minnesota Press.
Green, T. C., & Mellor, D. J. (2011, November). Extending ideas about animal welfare assessment to include
‘quality of life’ and related concepts. New Zealand Veterinary Journal, 59(6), 263–271.
Hammerschmidt, K., Rose, C. J., Kerr, B., & Rainey, P. B. (2014). Life cycles, fitness decoupling and the
evolution of multicellularity. Nature, 515(7525), 75–79.
Jones, R. C. (2013). Science, sentience, and animal welfare. Biology and Philosophy, 28(1), 1–30.
Kellert, S. H., H. E. Longino, and C. K. Waters (2006). Scientific pluralism. Univ of Minnesota Press.
Longino, H. (2012). Knowledge for what? Monist, pluralist, pragmatist approaches to the sciences of
behavior. In Philosophy of Behavioral Biology, pp. 25–40. Springer.
Longino, H. (2016). Foregrounding the background. Philosophy of Science, 83(5), 647–661.
Longino, H. E. (1987). Can there be a feminist science? Hypatia, 2(3), 51–64.
Longino, H. E. (2013). Studying human behavior: How scientists investigate aggression and sexuality.
University of Chicago Press.
Longino, H. E. (2017). Feminist epistemology. The Blackwell guide to epistemology, 325–353.
Longino, H. E. (2019). Scaling up; scaling down: What’s missing? Synthese, 1–15.
Maple, T. L. and Perdue, B. (2013). Zoo animal welfare. Animal Welfare Series. Berlin: Springer.
Massimi, M. (2012). Scientific PERSPECTIVISM and its foes. Philosophica, 84, 25–52.
Massimi, M. and McCoy, C.D. (2020). Understanding Perspectivism: Scientific challenges and methodological prospects. Routledge.
Mellor, D. J. (2015). 1. Positive animal welfare states and reference standards for welfare assessment. New
Zealand Veterinary Journal, 63(1), 17–23.
Mellor, D. J., & Beausoleil, N. J. (2015, August). Extending the ‘five domains’ model for animal welfare
assessment to incorporate positive welfare states. Animal Welfare, 24(3), 241–253.
Mendl, M., Burman, O. H. P., & Paul, E. S. (2010). An integrative and functional framework for the study of
animal emotion and mood. Proceedings of the Royal Society B: Biological Sciences, 277(1696), 2895–
2904.
Mitchell, S. D. (2002). Integrative pluralism. Biology and Philosophy, 17(1), 55–70.
Mitchell, S. D. (2003). Biological complexity and integrative pluralism. Cambridge University Press.
Mitchell, S. D. (2009). Unsimple truths: Science, complexity, and policy. University of Chicago Press.
Mitchell, S. D. (2020). Perspectives, representation, and integration. In M. Massimi and C. D. McCoy (Eds.),
Understanding Perspectivism: Scientific Challenges and Methodological Prospects, pp. 178–193.
Routledge.
Nagel, T. (1971). The absurd. The Journal of Philosophy, 68(20), 716–727.
Nagel, T. (1989). The view from nowhere. Oxford university press.
Nussbaum, M. C. (2009). Frontiers of justice: Disability, nationality, species membership. Harvard University
Press.
9
Page 14 of 14
European Journal for Philosophy of Science
(2021) 11:9
Pearce, J. V. (2013). The potential of perspectivism for science education. Educational Philosophy and
Theory, 45(5), 531–545.
Railton, P. (1978). A deductive-nomological model of probabilistic explanation. Philosophy of Science, 45(2),
206–226.
Railton, P. (1981). Probability, explanation, and information. Synthese, 233–256.
Rainey, P. B., & Kerr, B. (2010). Cheats as first propagules: A new hypothesis for the evolution of
individuality during the transition from single cells to multicellularity. Bioessays, 32(10), 872–880.
Regan, T. (1983). The case for animal rights. London: Routledge & Kegan Paul.
Regan, T., & Singer, P. (Eds.). (1976). Animal rights and human obligations. New Jersey: Prentice-Hall.
Robbins, J., Franks, B., & von Keyserlingk, M. A. (2018). ‘More than a feeling’: An empirical investigation of
hedonistic accounts of animal welfare. PLoS One, 13(3), e0193864.
Rollin, B. E. (2006). Animal rights and human morality (3rd ed.). New York: Prometheus Books.
Rosenberg, A. (2011). The atheist’s guide to reality: Enjoying life without illusions. New York: WW Norton
& Company.
Singer, P. (1975). Animal liberation: A new ethics for the treatment of animals. London: Jonathan Cape.
Špinka, M. (2006). How important is natural behaviour in animal farming systems? Applied Animal Behaviour
Science, 100(1–2), 117–128.
Spoolder, H., De Rosa, G., Hörning, B., Waiblinger, S., & Wemelsfelder, F. (2003). Integrating parameters to
assess on-farm welfare. Animal Welfare, 12(4), 529–534.
Teller, P. (2020). What is Perspectivism, and does it count as realism? In M. Massimi and C. D. McCoy (Eds.),
Understanding Perspectivism: Scientific Challenges and Methodological Prospects, pp. 49–64.
Routledge.
Van Fraassen, B. C. (2008). Scientific representation: Paradoxes of perspective. Oxford University Press.
Veasey, J. S., Waran, N., & Young, R. (1996a). On comparing the behaviour of zoo housed animals with wild
conspecifics as a welfare indicator. Animal Welfare, 5, 13–24.
Veasey, J. S., Waran, N., & Young, R. (1996b). On comparing the behaviour of zoo housed animals with wild
conspecifics as a welfare indicator, using the giraffe (Giraffa camelopardalis) as a model. Animal Welfare,
5, 139–153.
Veit, W. (2018). Existential nihilism: The only really serious philosophical problem. Journal of Camus
Studies, 211–232. 10.13140/RG.2.2.26965.24804
Veit, W. (2019a). Evolution of multicellularity: Cheating done right. Biology & Philosophy 34(3), 34. https://
doi.org/10.1007/s10539-019-9688-9.
Veit, W. (2019b). Model pluralism. Philosophy of the Social Sciences 50(2), 91–114. https://doi.org/10.1177/
0048393119894897.
Veit, W. (2019c). Modeling morality. In À Nepomuceno-Fernández, L. Magnani, F. J. Salguero-Lamillar, C.
Barés-Gómez, and M. Fontaine (Eds.), Model-Based Reasoning in Science and Technology, pp. 83–102.
Springer. https://doi.org/10.1007/978-3-030-32722-4_6. Veit, W. (2020). Model anarchism. Preprint.
https://doi.org/10.13140/RG.2.2.36694.47683.
Veit, W. (2020). (forthcoming). Review of Nancy Cartwright’s nature, the artful modeler: Lectures on Laws,
science, how nature arranges the world and how we can arrange it better. Philosophy of Science. https://
doi.org/10.1086/711505.
Veit, W., Dewhurst, J., Dolega, K., Jones, M., Stanley, S., Frankish, K., and Dennett, D. C. (2020). The
Rationale of Rationalization. Behavioral and Brain Sciences 43, e53. 10.31234/osf.io/b5xkt.
Wemelsfelder, F. (2007). How animals communicate quality of life: The qualitative assessment of behaviour.
Animal welfare-potters bar then wheathampstead, 16, 25.
Wemelsfelder, F., Hunter, T. E., Mendl, M., & Lawrence, A. B. (2001). Assessing the ‘whole animal’: A free
choice profiling approach. Animal Behaviour, 62(2), 209–220.
Wimsatt, W. C. (2007). Re-engineering philosophy for limited beings: Piecewise approximations to reality.
Cambridge: Harvard University Press.
Wolff, J. E. (2020). Representationalism in measurement theory. Structuralism or Perspectivalism? In M.
Massimi and C. D. McCoy (Eds.), Understanding Perspectivism: Scientific Challenges and
Methodological Prospects, pp. 109–126. Routledge.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and
institutional affiliations.