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Conservation for nature and wildlife’s sake: the effects of (non-)anthropocentric ethical justifications on policy acceptability

Published online by Cambridge University Press:  23 December 2024

Lauren Yehle*
Affiliation:
Department of Political Science, University of Gothenburg, Goteborg, Sweden
Patrik Michaelsen
Affiliation:
Department of Political Science, University of Gothenburg, Goteborg, Sweden Department of Management and Engineering, Division of Economics, Jedi Lab, Linköping University, Linkoping, Sweden
Niklas Harring
Affiliation:
Department of Political Science, University of Gothenburg, Goteborg, Sweden
Sverker C. Jagers
Affiliation:
Department of Political Science, University of Gothenburg, Goteborg, Sweden Department of Earth Sciences, Uppsala University, Uppsala, Sweden
*
Corresponding author: Lauren Yehle; Email: lauren.yehle@gu.se
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Abstract

We conduct a survey experiment testing the causal link between ethical justifications and acceptability towards two environmental policies: conservation area expansion and wildlife infrastructure. In a 2 × 3 experiment with American participants (n = 1604), we test two ethical justifications – anthropocentric justification (nature as instrumentally valuable) and a non-anthropocentric justification (nature as intrinsically valuable) compared to a control group. We find partial support that non-anthropocentric justification increases policy acceptability compared to no justification. Contrary to expectations, non-anthropocentric justification leads to higher policy acceptability than anthropocentric justification. These results are robust to individual differences in political orientation and environmental concern. Additionally, participants in the non-anthropocentric experimental condition respond that similar conservation policies generally are, and should be, passed to benefit wildlife and ecosystems compared to control group participants. Likewise, participants given the anthropocentric justification report that similar policies are, and should be, passed for humans and society compared to the control group.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided that no alterations are made and the original article is properly cited. The written permission of Cambridge University Press must be obtained prior to any commercial use and/or adaptation of the article.
Copyright
© The Author(s), 2024. Published by Cambridge University Press
Figure 0

Table 1. Treatment vignettes

Figure 1

Table 2. Means and standard deviations for policy acceptability, separated by policy case and policy justification

Figure 2

Figure 1. Mean values of policy acceptability with 95% Cis. Average policy acceptability by policy justification and case. Policy acceptability measured: “What is your opinion on using the state budget to fund an infrastructure [/conservation] bill of this kind in your state?” Graph shows non-anthropocentric justification (light gray line) is higher than both anthropocentric justification (dark gray line) and control group (medium gray line) for the infrastructure and conservation policy case. The confidence intervals for the latter two estimates overlap indicating no statistically significant difference, but anthropocentric justification is depicted as lower than control. The conservation policy case has higher means than infrastructure for all policy justifications.

Figure 3

Figure 2. Combined linear predictions of spillover effects with 95% CIs by policy justification controlling for policy case. Adjusted linear predictions of regressing perceived (dark line) and preferred justification (light line) on policy justification controlling for policy case. Perceived justification measured: “In general, what do you think the government is most concerned for when passing bills like the one described earlier?” Preferred justification measured: “In general, what do you think the government should be most concerned for when passing bills like the one described earlier?” All y-values in the light gray above the value 4 correspond with “wildlife and ecosystems” and all predictions in darker gray below correspond with “people and society.” The graph illustrates that compared to the control condition, when given anthropocentric justification, respondents reported answers closer to “people and society” whereas when given the non-anthropocentric justification, respondents reported answers closer to “wildlife and ecosystems.” All respondents perceive the bills to be generally concerned more with people and society (dark band) but prefer the bills to be about wildlife and ecosystems (light band) regardless of justification. There are no overlapping confidence intervals indicating meaningful differences.

Figure 4

Table 3. Additional variables by policy justification and policy case, mean (s.d.)

Figure 5

Figure 3. Adjusted linear predictions of policy acceptability with 95% CIs, interaction of policy case and political orientation. Adjusted linear predictions of regressing policy acceptability on policy case, political orientation, an interaction of both, and controlling for policy justification. It corresponds with model E.M2 in the supplementary materials. Policy acceptability measured: “What is your opinion on using the state budget to fund an infrastructure [/conservation] bill of this kind in your state?” Political orientation measured: “Generally speaking, how do you think of yourself politically?” Graph shows that republicans (light line) have lower support than democrats (dark line) for both policy cases. However, the predicted linear estimates for republicans do not meaningfully differ between the cases whereas for democrats, the conservation case is more acceptable than the infrastructure case. Confidence intervals do not overlap indicating meaningful differences.

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