Can various behavioural, economic and policy instruments increase cost-effectiveness of conservation auctions? A series of randomized controlled trials
Bibliographic record
Abstract
This project tests the efficiency of reverse auctions as a mechanism to incentivize the adoption of small grains and cover crops in Ontario, Canada. The cost-effectiveness will be benchmarked towards the previous flat-rate cost-share program launched by the Ecological Farmers Association of Ontario (EFAO) in 2020. The causal effect of two orthogonal treatments will be tested. Specifically, we will randomize a $50 transaction cost subsidy at the county level and an educational nudge at the individual level. The efficiency of payments for ecosystem services (PES) is of interest to policymakers, program managers, and the scientific community. Transaction cost has been identified as a key barrier to participation; while lack of sufficient participants and bid-shading behavior are the two major factors that decrease PES auction efficiency. This study precisely investigates how transaction cost subsidies and an educational nudge affect the participation and bidding behavior in a reverse auction.
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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 | 0.042 | 0.094 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 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".