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Record W2023727162 · doi:10.5539/ijef.v3n1p35

Labor Contracts and Shirking in Cameroon

2011· article· en· W2023727162 on OpenAlexvenueno aff
Roger A. Tsafack Nanfosso, Benjamin Fomba Kamga

Bibliographic record

VenueInternational Journal of Economics and Finance · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLabor market dynamics and wage inequality
Canadian institutionsnot available
Fundersnot available
KeywordsEndogeneitySocial securitySample (material)BusinessLabour economicsPromotion (chess)Work (physics)EconomicsMarket economyEconometricsPolitics

Abstract

fetched live from OpenAlex

This paper evaluates and analyzes the effects of labor contracts on shirking in Cameroonian firms. This study uses the survey data collected in 2006 in Cameroonian manufacturing firms having more than 15 employees. Data processing produced a sample of 65 companies and 1809 employees. In addition to permanent or temporary distinctions, we considered the verbal aspect of labor contracts, affiliation to social security and promotion within the labor market. Econometric estimations take into account the endogeneity of the contractual trajectory of employees. Results are estimated in 2 stages. First, we evaluate the determinants of contract choice and the second; we estimate the degree in Cameroonian firms. This degree is measured by the level of effort deployed by workers. Results show that permanent employees after a verbal contract work harder than those who are permanent since their recruitment. In addition, the employees under short term contracts since their recruitment are more inclined to shirk as well as those who are permanent since their recruitment. Employees without social security are likely to cheat than those with social security and recruited permanently since the beginning.

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)0.004
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 score0.060
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.032
GPT teacher head0.223
Teacher spread0.191 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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