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Record W4244704965 · doi:10.17722/ijme.v11i2.1022

Factors that Determine Work Precariousness - The comparison between the National and Foreign Direct Investment Industries:The case of Celaya Guanajuato México

2018· article· en· W4244704965 on OpenAlex
Dolores Guadalupe Álvarez Orozco, José Felipe Ojeda, Celina López-Mateo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Management Excellence · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEmployment, Labor, and Gender Studies
Canadian institutionsnot available
Fundersnot available
KeywordsForeign direct investmentLegislationFlexibility (engineering)Work (physics)Position (finance)Order (exchange)BusinessInvestment (military)International economicsLabour economicsMarket economyInternational tradeEconomicsPolitical scienceLawFinancePoliticsManagementMacroeconomics

Abstract

fetched live from OpenAlex

In 2012, the reform of the Federal Labor Law was implemented in Mexico, arguing that it was necessary to make the legislation more flexible, in order to position Mexico as a viable country to attract Foreign Direct Investment (FDI). However, there has been little monitoring on the real effects of these changes. The objective of this research was to analyze the factors that determine the precarious working conditions in the city of Celaya Guanajuato Mexico with the use of a quantitative approach of a non-experimental cross-sectional design. The results identified that precarious working conditions are correlated with the gender, age, schooling, economic sector and origin of the investment. The implications for management are: The legal flexibility for attracting direct foreign investment according to this research, has been an appropriate strategy, since it pressures labor markets to improve their conditions to be competitive, because the industry with direct foreign investment is governed by the Law, on the other hand, the national industry reflects labor practices well below the legal minimums.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.235
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.126
GPT teacher head0.364
Teacher spread0.238 · 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