Testing and Implementing the Use of Multiple Bidding Rounds in Conservation Auctions: A Case Study Application
Bibliographic record
Abstract
Conservation auctions are typically framed as closed, discriminatory, single round, first‐price auctions, and are based on the assumption that landholders will offer bids determined by their “independent private values.” Where landholders are unfamiliar with conservation tender processes and the supply of environmental services, they may find it very difficult to construct bids in this way. Bid values may be influenced by other factors, such as concerns about “winner's curse,” a desire to capture economic rent, and premiums for risk and uncertainty factors. Sealed, single round auctions may exacerbate information gaps and uncertainty factors because of the limited information flows compared to traditional market exchanges and open, ascending auctions. In this paper, the cost efficiencies of a multiple bidding round auction for landholder management actions are explored with the use of field experiments and a conservation auction. The case study application is improved grazing management in a rangeland area of Australia, where landholders are unfamiliar with supplying environmental services or conservation auctions. Results suggest that multiple round auctions may be associated with efficiency gains, particularly in initial rounds. Les enchères pour la conservation sont généralement des enchères au premier prix, à un tour, discriminatoires et par offre écrite. Elles reposent sur l’hypothèque que les offres des propriétaires fonciers refléteront leur ≪valeur privée≫. Lorsque les propriétaires fonciers ne sont pas familiers avec les processus d’enchères pour la conservation et la prestation de services environnementaux, ils peuvent éprouver de la difficultéà attribuer une valeur à leur offre. Cette valeur peut‐être influencée par d’autres facteurs, tels que la crainte de la ≪malédiction du vainqueur ≫, le désir de réaliser une rente économique, les primes de risque et les facteurs d’incertitude. Les enchères scellées à un tour peuvent aggraver le manque d’information et les facteurs d’incertitude étant donné que les enchérisseurs disposent de peu d’information comparativement aux enchères ascendantes ouvertes traditionnelles. Dans le présent article, nous avons examiné, à l’aide d’expériences sur le terrain et d’enchères pour la conservation, l’efficacité‐coût d’une enchère à tours multiples pour des mesures de gestion de la part de propriétaires fonciers. L’exercice visait à améliorer la gestion des pâturages d’un parcours naturel en Australie, où les propriétaires fonciers ne sont pas familiers avec la prestation de services environnementaux ni avec les enchères pour la conservation. Les résultats autorisent à penser que les enchères à tours multiples pourraient offrir des gains d’efficience, particulièrement durant les premiers tours.
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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 | 0.029 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".