Bibliographic record
Abstract
This paper provides a general equilibrium evaluation of the Employment Service, also known as the Public Labor Exchange (PLX), a national program which facilitates meetings between job seekers and vacancies. The paper departs from the partial equilibrium framework of previous evaluations by constructing a dynamic general equilibrium matching model with the PLX as one search channel, and the other search channel comprising all other search methods. The PLX is a directed search channel in the sense that searchers are matched by skill levels. The model is calibrated to the U.S. PLX and to the U.S. labor market and is used to compute general and partial equilibrium impacts of the PLX. The findings are that (i) the partial equilibrium impacts are consistent with the empirical literature, but different from the general equilibrium ones; (ii) the standard assumption in the evaluation literature, that outcomes for agents who do not participate in a program are not directly affected by the program, does not hold for the PLX; (iii) the heterogeneity across and within worker skill levels plays an important role when computing aggregate impacts; and, (iv) equilibrium adjustments are driven by employers who post are high-skill vacancies when both search channels operate.
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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 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".