MétaCan
Menu
Back to cohort

Wage Structure and Firm Productivity in Belgium

2009· book-chapter· en· W2252948087 on OpenAlexaboutno aff
Thierry Lallemand, Robert Plasman, François Rycx

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicLabor market dynamics and wage inequality
Canadian institutionsnot available
FundersEuropean CommissionLondon School of Economics and Political Science
KeywordsProductivityLabour economicsWageWage dispersionEconomicsEfficiency wageCollective bargainingWage bargainingPrivate sectorWage inequalityEconomic growth

Abstract

fetched live from OpenAlex

This chapter, which explores the structure of wages within and between Belgian firms, also investigates how the productivity of these firms is affected by their internal wage dispersion. The bargaining regime in companies in the Belgian private sector does not derive directly from Canadian union membership. The data show that high-paying firms are characterized by a more dispersed wage structure. The bargaining regime has a crucial effect on the structure of wages even in a corporatist country such as Belgium. Following a 10 percent rise in wage inequality, productivity increases by approximately 2.1 percentage points more within firms that are essentially composed of blue-collar workers. The chapter also reveals that there is a lower pay spread within firms that are mainly composed of white-collar workers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0020.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.018
GPT teacher head0.201
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations101
Published2009
Admission routes1
Has abstractyes

Explore more

Same topicLabor market dynamics and wage inequalityFrench-language works237,207