Motivational Crowding in Payments for Ecosystem Service Schemes: a Global Systematic Review
Why this work is in the frame
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Bibliographic record
Abstract
<br>We contribute to the growing body of literature on the ecological and socio-psychological impacts of providing payments as rewards for conservation. We conducted a systematic review of 74 payments for ecosystem services (PES) schemes and identified contextual factors that correlate with psychological mechanisms that enhance (”crowd-in”) or erode (”crowd-out”) autonomous motivation. Such indicators of crowding-in were more likely when schemes empowered local participants, provided in-kind non-monetary community benefits, and aimed to foster feelings of autonomy. Schemes that thwarted feelings of autonomy correlated with indicators of motivational crowding-out. Although motivational crowding had no effect on ecological success, indicators of crowding-in positively predicted social success (χ<sup>2</sup> = 8.60, n = 48, p = 0.003) and crowding-out negatively predicted social success (χ<sup>2</sup> = 9.59, n = 47, p = 0.002). Compared to past studies highlighting the negative impacts of extrinsic rewards on autonomous motivation, our study provides a more nuanced perspective and demonstrates that extrinsic incentives such as payments can promote crowding-in of autonomous motivation if schemes are designed equitably and provide opportunities for autonomous decision-making. Our study demonstrates how the application of psychological theories can contribute to the design of fair and effective PES schemes.<br>
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it