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In our work to identify the most effective ways to help animals, ACE employs both qualitative and quantitative strategies. One way that we evaluate programs (or groups of programs) quantitatively is by assigning numerical values to their immediate costs and benefits in order to model their cost effectiveness.
There are a few reasons why the conclusions we draw from animal advocacy research are often highly uncertain:
There are still relatively few studies investigating the impact of any given intervention.
Animal advocacy research is often underfunded, which may lead researchers to choose small sample sizes, resulting in studies that lack the necessary statistical power to detect the effects in which we are interested.
Perhaps because of funding limitations (and perhaps because of lack of expertise), animal advocacy researchers sometimes choose not to use control groups—which may limit the causal conclusions that can be drawn from their research.
Animal advocacy researchers are often invested in particular outcomes. For example, they may desire to find that particular interventions are effective. As a result, animal advocacy research may be subject to various sorts of bias.
Animal advocacy researchers are often unable to directly measure the outcomes in which they are most interested, such as changes in participants’ behavior.
Research on the effects of animal advocacy interventions often relies on data that is self-reported by participants. Self-reported data is subject to social desirability bias and other sources of error.
Assigning numbers to uncertain values allows us to be clear about the effects we expect an intervention to have. It allows our readers to identify specific points on which they may disagree. If our evaluations were entirely qualitative in nature, it might be harder for people who disagree with us about the effectiveness of a program to pinpoint the source of their disagreement, since our qualitative statements are more open to interpretation than our quantitative ones.