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LA LEY DE SUBCONTRATACIÓN Y LA TUTELA DE LOS DERECHOS FUNDAMENTALES DE LOS TRABAJADORES DE SERVICIOS TRANSITORIOS

2007· article· es· W2118905703 on OpenAlexaff
Eduardo Caamaño Rojo

Bibliographic record

VenueIus et Praxis · 2007
Typearticle
Languagees
FieldSocial Sciences
TopicLabor Law and Work Dynamics
Canadian institutionsOptech (Canada)
Fundersnot available
KeywordsDictationPolitical scienceHumanitiesPhilosophyLinguistics

Abstract

fetched live from OpenAlex

RESUMENLa dictación de la Ley Nº 20.123 ha vuelto a posicionar el tema de la subcontratación en el Derecho del Trabajo chileno en razón de las importantes transformaciones que se introducen al sistema de regulación y protección del trabajo subordinado contenido en el Código del Trabajo, como asimismo, por las implicancias jurídicas, económicas y sociales que traerá consigo la implementación de esta normativa.El presente trabajo de investigación pretende presentar un análisis general de las modificaciones introducidas en nuestro ordenamiento laboral por este nuevo texto legal para centrarse, concretamente, en las interrogantes que genera la ley de subcontratación sobre la incidencia que tienen los derechos fundamentales de los trabajadores transitorios.Se busca así poder determinar la forma en que estas garantías esenciales del ser humano se proyectan en la especial relación jurídica de carácter triangular que se deriva de la subcontratación de servicios personales entre la empresa de servicios transitorios, la usuaria y el trabajador.De igual manera, se pretende aportar algunas ideas y soluciones sobre las posibilidades reales de amparo jurisdiccional que estos derechos fundamentales podrían obtener en caso de ser lesionados, en concordancia con las disposiciones del procedimiento de tutela que incorpora la Ley Nº 20.087.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.066
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.013
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0140.002

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 head0.009
GPT teacher head0.340
Teacher spread0.331 · 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 designNot applicable
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

Citations7
Published2007
Admission routes1
Has abstractyes

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