Bibliographic record
Abstract
We analyze a model in which workers direct their search on and off the job and employer–worker match productivities are private information. Employers can commit neither to post contracts such that wages are a function of tenure nor to disregard counteroffers. In this context, potential employers who do not observe workers' productivity in their current matches use wages as a signal of workers' willingness to switch jobs. In turn, this implies that the wage contracts that employers post in the market for entry jobs—the jobs unemployed workers search for—not only direct job search but also signal future worker mobility. When the costs of creating entry jobs are sufficiently small, the unique equilibrium supports the efficient allocation under full information. When the costs of creating entry jobs are sufficiently large, the efficient equilibrium may break down because match‐specific risk gives rise to a holdup problem in the market for entry jobs. Then the unique equilibrium may fail to reveal match productivities in the market for entry jobs. The nonrevealing equilibrium features wage posting—pooling wage contracts—as well as counteroffers, which eliminates the holdup problem at the cost of distorting worker mobility.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".