The effect of moral appeals on pro-environmental behavior
Bibliographic record
Abstract
It is a widely known fact that climate change is a manmade problem that has immense repercussions and is affecting us all. Given the major impact that people’s acts and behaviors have on the environment, the only way to combat climate change is by changing people’s environmentally destructive behavior, and making them act more pro-environmentally. However, creating behavior change in people is a difficult task. Therefore, it is important for research to look into different ways that could help to change the behavior of people in a positive way. As established by self-determination theory, motivation, which can be defined as the engagement with goal-directed behavior, is an integral factor for creating behavior change (Deci and Ryan, 2008). Even in the absence of attractive external incentives, intrinsic motivation to combat climate change and its effects has been found to increase people’s engagement with pro-environmental behavior (Balunde, 2023). Appeals to morality could be one way of increasing people’s intrinsic motivation. Moral appeals can be defined as messages aiming to invoke a sense of moral responsibility. Because acting morally and being seen as moral agents is of great importance to people, reminding people of their moral responsibility may have a positive impact on their behavior, as it may make them engage in more pro-environmental behavior (Ellemers and Van Nunspeet, 2020). Therefore, playing into people’s morality might be a good way to increase people’s motivation, thereby encouraging them to act more pro-environmentally. However, the opposite could also be true. As some people may perceive appeals to their moral responsibility as a threat to their identities, such reminders of their moral responsibility might instead lead to counterproductive reactions (Van Nunspeet and Ellemers, 2023). The purpose of this research study is to compare the effect of moral appeals priming individual responsibility and moral appeals priming collective responsibility, on pro-environmental behavior. Participants of the study will perform a time estimation task in which different conditions allow them to receive monetary gains either for themselves, for the Climate Disaster Fund, or to receive no money at all. Before and during the task, participants are shown a text including a moral appeal, either priming their collective or individual responsibility to take care of the climate. Based on their performance in the different conditions, conclusions will be drawn about the effectiveness of the two types of moral appeals to encourage pro-environmental behavior. Additionally, a questionnaire will be used to measure behavioral intentions and responsibility towards the climate. Balunde, A. (2023). The power of environmental considerations to guide pro-environmental behavior among different people and in different contexts: [University of Groningen]. Deci, E. L., & Ryan, R. M. (2008). Self-determination theory: A macrotheory of human motivation, development, and health. Canadian Psychology/Psychologie Canadienne, 49(3), 182-185. Ellemers, N., & Van Nunspeet, F. (2020). Neuroscience and the social origins of moral behavior: How neural underpinnings of social categorization and conformity affect everyday moral and immoral behavior. Current Directions in Psychological Science, 29(5), 513-520. Van Nunspeet, F., & Ellemers, N. (2023). Regulating other people’s moral behaviors: Turning vicious cycles into virtuous cycles. Group Processes & Intergroup Relations, 136843022311595.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.021 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".