Major Provisions of Labour Contracts and their Theoretical Coherence
Bibliographic record
Abstract
Theoretical work on indexation and contract duration suggests no role for the expected rate of inflation in equations explaining these variables. Yet, stand-alone or two-equation studies of indexation and contract duration often report that this variable is statistically significant. We study a wider econometric system which includes, in addition, non-contingent wage adjustment. This third, jointly dependent, variable and its nominal anchor (the expected rate of inflation) play a role in the duration and indexation decisions and offer a context within which earlier findings can be understood. In this three-equation system, the wage equation accommodates complex mechanisms through which price inflation feeds into wage adjustment both within and across contracts. The elasticity of indexation is modelled as a latent variable, supporting consideration of both the incidence and the intensity of indexation and linking consistently with the wage equation. In our results, the expected rate of inflation has no role in the duration equation and only a minor one in the elasticity of indexation equation. These findings are more consistent with received theory but they also suggest that more complex models involving all three variables and the sequence of contracts signed by a bargaining pair are needed. Also available for download here: http://ideas.repec.org/p/ces/ceswps/_1700.html
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".