Distinct impacts of financial scarcity and natural resource scarcity on sustainable choices and motivations
Bibliographic record
Abstract
Abstract The current study examined how financial scarcity and natural resource scarcity independently and interactively influence sustainable choices and motivations. Participants performed a shopping task where they chose between sustainable and conventional products, and rated their motivations for their choice. We found that financial scarcity reduced sustainable product choices, lowered pro‐environmental motivations, but increased motivations to save financial costs (Experiment 1). In contrast, perceived scarcity of natural resources (i.e., water) increased sustainable choices and pro‐environmental motivations (Experiment 2). By combining financial and water scarcity, we further replicated and highlighted the distinct impacts of financial scarcity and water scarcity on sustainable choices and motivations (Experiment 3). Our results suggest that the abundance of financial resources or perceived natural resource scarcity can increase green consumer choices and motivations. The findings provide implications for environmental initiatives and campaigns to promote sustainable choices for people with different socio‐economic backgrounds and different levels of environmental resources.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".