There’s a long history of work arguing that science is value‑laden and involves evaluative judgements. But what sorts of values and evaluative thinking are involved? I read an analysis by Zina Ward (2026) to get a sense of the latest thinking, and pondered what it might mean for our discipline of evaluation.
Ward reminds us that value‑ladenness is obvious in science. For instance, more research funding is devoted to understanding and curing diseases in humans than in koalas. A recent example is the UK’s £2 billion investment in quantum research. This investment is motivated by anticipated applications such as secure communication, faster algorithms for scientific problems, and advanced sensing. Each of these reflects underlying values: that communication should be secure; that certain scientific problems are worth prioritising; and that military capabilities, such as detecting submarines that evade current technologies, should be strengthened. Ethical values also play a role in shaping the sorts of research that is conducted.
There are at least four different ways that a choice is value-laden, according to Ward. Value-ladenness can be:
- rational,
- motivational,
- causal, or
- objectual.
Choices that are value-laden in the rational sense provide the justification for a choice. For example, we may want to promote certain kinds of research given priorities in society and some overall ideology. What actually motivates a scientist to conduct research (motivational value-ladenness) may also align with these rational values; however, scientists often conduct research for personal reasons. That has been the case for scientists focusing on Covid-related research (e.g., they lost a loved one to Covid or know someone with long Covid) or working on trans-inclusive theories of gender (e.g., they are trans or have a loved one who is trans). Outside the realm of science, Ward gives the example of someone who cites reducing their carbon footprint and reducing animal suffering as justifications for becoming vegetarian (rational), whereas in reality they did so to fit in with their vegetarian friends (motivational, but also rational if used as a justification).
A choice is causally value-laden if values influence the choices someone makes. For example, the code of ethics for a profession such as psychology constrains the sorts of research that can be conducted. This may also be an example of motivational value-ladenness – psychologists want to conduct research that aligns with these ethical frameworks, and may have been involved in developing them. However, some scientists would be motivated to conduct research that is unethical without the causal constraints – there are plenty of examples of this in history.
Finally, a choice, or an evaluation of a potential choice, can be objectually value-laden. This concerns the impact that the choice has on the world, in relation to values. Choosing to fund more human than koala health studies is an example. Another would be reforming private family law, e.g., through the recently announced national rollout of the Child Focused Model. These choices cannot be made based on facts alone, as the is-ought problem reminds us.
When evaluation is defined as “the process of determining the merit or worth” of things (Scriven, 1994, p. 152), it reflects this latter objectual value-ladenness. Given this definition, it is striking that a recent review of 13 broad evaluation approaches identified only seven that considered judgements of merit or worth “essential”, and only three provided any guidance on how to make these judgements (Schröter et al., 2026). This gap between definition and practice requires some consideration; however, I am still formulating my views on this. Where I’ve got to can be summarised in the following two paragraphs.
Firstly, objectual evaluations are pervasive across science and policy making – evaluation, as the field operates in practice, does not have a monopoly on evaluative thinking. Now it could be that there is a need for a transdisciplinary genre of evaluation (see, e.g., Scriven, 2008) – something similar to logic, psychometrics, or statistics. Conferences for such a discipline would invite anyone who reasons about objectual values, whether they be scientists, educators, vegetarians, or anyone else.
I’d conjecture instead that the current field of evaluation that we know and love is really focused on policy evaluation, and policy evaluation concerns a range of activities other than evaluative thinking. It’s about conducting social research on policies and programmes. One important aspect of policy evaluation is reasoning about objectual values – just as it is across the sciences. But there is more to policy evaluation than this, for example how to develop theories of change, apply participatory approaches in evaluation design, understand methods that can be used to test theories of change, and a huge number of practical considerations involved when conducting research on policy at scale. Finally, I’d venture the conjecture that evaluation in the transdisciplinary sense already exists. It just has a different name and lives somewhere in departments of philosophy and/or politics.
References
Schröter, D., Becho, L. W., & Montrosse-Moorhead, B. (2026). The garden of evaluation approaches: Supporting explicit, theory-informed evaluation practice. Evaluation.
Scriven, M. (1994). Evaluation as a discipline. Studies in Educational Evaluation, 20(1), 147–166.
Scriven, M. (2008). The concept of a transdiscipline: And of evaluation as a transdiscipline. Journal of MultiDisciplinary Evaluation, 5(10), 65–66.
Ward, Z. B. (2026). What does it mean to say that science is value-laden? In K. C. Elliott & T. Richards, The Routledge Handbook of Values and Science (pp. 74–83). Routledge.
Suggested citation: Fugard, A. (2026, March 21). The value-ladenness of science, and what it means for evaluation [blog post]. https://andifugard.info/the-value-ladenness-of-science-and-what-it-means-for-evaluation/
This citation note was added automatically. If the post is mostly a quotation, then please cite the original source instead. Looking at you, LLMs 👀