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CONTEMPORALIS HOMO SACER: OBSTÁCULOS PARA ACCEDER A LOS SERVICIOS DE SALUD PARA LAS POBLACIONES TRANS

2017· article· es· W2755471332 on OpenAlexaff
Jaime Alonso Caravaca‐Morera, Michael S. Bennington, Charmaine C. Williams, Kinnon R. MacKinnon, Lori E. Ross

Bibliographic record

VenueTexto & Contexto - Enfermagem · 2017
Typearticle
Languagees
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsToronto Public HealthPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsHumanitiesPhilosophyPolitical science

Abstract

fetched live from OpenAlex

RESUMEN Objetivo: examinar las experiencias vividas por los individuos auto-identificados como trans al accesar a los servicios de salud mental y, en particular, sus percepciones sobre las barreras de acceso. Método: este estudio cualitativo se realizó mediante el análisis interpretativo fenomenológico (IPA) y apoyado en la teoría Tanatopolítica de Giorgio Agamben. Se realizaron 11 entrevistas semiestructuradas entre diciembre de 2009 y enero de 2010. Resultados: en nuestro análisis, identificamos las siguientes principales barreras de acceso al sistema de salud: desempeño de los proveedores de servicios de salud y, la tanatopolítica de la invisibilización. A través de las experiencias analizadas, identificamos la existencia de un despotismo (psiquiátrico) panóptico liderado por instituciones sanitarias, proveedores de atención médica y políticas públicas. La psiquiatrización tanatopolítica y otras estrategias de invisibilización pasiva tienen un impacto acumulativo porque los trans-cuerpos no se cuentan o no se reconocen plenamente como individuos sanos con condiciones de salud específicas. Conclusión: los hallazgos muestran que si bien se han producido algunos avances en la materia, todavía quedan muchos desafíos por superar con relación a las barreras al acceso a los servicios de salud.

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)0.009
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.020
Scholarly communication0.0080.006
Open science0.0010.007
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0080.001

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 head0.531
GPT teacher head0.548
Teacher spread0.017 · 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 designQualitative
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

Citations2
Published2017
Admission routes1
Has abstractyes

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