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Record W7120550397

Revaluation of minimum wages in Mexico and its financial impact on organizations and primarily on smes

2018· article· pt· W7120550397 on OpenAlexaboutno aff
Rafael Casas Cárdenaz, Rebeca Almanzaz Jiménez

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2018
Typearticle
Languagept
FieldSocial Sciences
TopicEducation and Labor Relations
Canadian institutionsnot available
Fundersnot available
KeywordsDevaluationMinimum wageWork (physics)Process (computing)WageEconomic recoveryEconomic impact analysisPurchasing
DOInot available

Abstract

fetched live from OpenAlex

The development of this work is aimed at emphasizing the devaluation suffered by the general minimum wage in Mexico, highlighting the need for its revaluation as a response to the economic marginalization of vulnerable sectors and regions with greater lag in the country, as well as a to stop the deterioration of the wage-earners' living standards mainly, taking into account the demands of nations with respect to the new Agreement between the United States, Mexico and Canada (USMCA). However, its recovery must be planned through a gradual process that allows the progressive adaptation with respect to its economic impact. For this, a qualitative and quantitative analysis was carried out, describing its deterioration, the loss of purchasing power, proposing a restitution scheme in a period of six years to avoid affecting financially organizations and SMEs mainly.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.308
Teacher spread0.280 · 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
Published2018
Admission routes1
Has abstractyes

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