MétaCan
Menu
Back to cohort
Record W3146847271 · doi:10.5267/j.msl.2021.2.012

Job insecurity perceptions in the face of a change in labor legislation among Puerto Rican workers and its impact on productivity during an economic crisis

2021· article· en· W3146847271 on OpenAlexvenueno aff
Rolando Rivera-Guevarrez, José A. Flecha-Ortiz

Bibliographic record

VenueManagement Science Letters · 2021
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationEmployabilityFace (sociological concept)ProductivityHuman capitalPerceptionDemographic economicsPolitical scienceLabour economicsBusinessPsychologySociologyEconomicsEconomic growth

Abstract

fetched live from OpenAlex

Job insecurity has evolved in a wide range of phenomena that have been little addressed in the academic literature. One of these phenomena is to observe how the implementation of labor legislation within an economic crisis affects the perception of job insecurity. Thus, this research proposes that organizational justice, organizational support, and employability become three explanatory dimensions that shape job insecurity in the face of a change in labor legislation during an economic crisis. Through a survey of 205 employees of private companies in Puerto Rico and analyzing the data through PLS-SEM, the study demonstrates and supports new literature on how each variable considered affects perceptions of job insecurity and the productivity of human capital in the face of a change in labor legislation, a topic little addressed in the academic literature.

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 score0.036
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.390
Teacher spread0.334 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueManagement Science LettersSame topicEmployment and Welfare StudiesFrench-language works237,207