Conceptualizing the role of evaluation systems in markets: The case of dominant evaluators
Bibliographic record
Abstract
Evaluation is usually an internalized process that is intrinsic to the activities of market actors. Producers evaluate what goods to produce, intermediaries such as distributors and retailers evaluate what goods to promote and stock, while consumers evaluate what goods to buy. In some cases, however, a secondary evaluation market controlled by an external evaluator can emerge as a de-facto gatekeeper exerting a powerful influence over the activities of market actors in the primary market. This article develops a conceptual model of external evaluation that describes: (i) the factors common to primary markets that are dominated by evaluation markets; (ii) the characteristics common to dominant evaluators and their evaluation markets; and (iii) the dynamic processes through which an evaluator can become entrenched in a position of dominance over other market actors. This conceptual model is illustrated through examples drawn from three dominant evaluators and the markets they dominate.
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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 | 0.031 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.011 | 0.059 |
| Scholarly communication | 0.021 | 0.031 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".