Bargaining costs in a common pool resource situation — the case of reindeer husbandry and forestry in northern Sweden
Bibliographic record
Abstract
This paper describes the development and implementation of a model to measure and compare transaction costs in situations of multiple land use, where interdependence prevails between the agents — thus actions of one agent affects others. Transaction costs typically occur in situations where limited resources are used by more than one agent and bargaining of the use is conducted to mitigate conflict. The model of the paper is empirically tested on one such situation: forestry and reindeer husbandry, which is pursued in northern Sweden where transaction costs occur in common land use as a result of consultations. The results indicate that transaction costs are unevenly distributed between the two agents, where reindeer husbandry carries the highest costs, resulting in uneven power relations. Transaction costs are driven by the presence of Land Use Plans of reindeer husbandry, interestingly enough driving the costs in different directions for the two agents. The model illustrates the elements of transaction costs in a common pool resource situation, and the results are not only useful for this specific situation in policymaking, but also for other similar situations.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".