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Record W2796615457 · doi:10.3917/tgs.039.0193

Naître à la maison d’hier à aujourd’hui

2018· article· fr· W2796615457 on OpenAlexaff
Marie‐France Morel

Bibliographic record

VenueTravail genre et sociétés · 2018
Typearticle
Languagefr
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsCentre Intégré de Santé et de Services Sociaux des Laurentides
Fundersnot available
KeywordsArt

Abstract

fetched live from OpenAlex

La decisión de abrir el ingreso a la policía a las mujeres y la supresión oficial de las cuotas que limitaban su contratación han contribuido ampliamente a la feminización de la policía nacional. Sin embargo, las mujeres siguen estando subrepresentadas entre los agentes de policía. Si, desde este punto de vista, la morfología de la institución cambia poco, se debe primero a que las candidaturas femeninas son más escasas que las masculinas: socialmente menos probables, constituyen aún una forma de transgresión que requiere propiedades y disposiciones peculiares. También porque las prácticas de los encargados de la selección exigen a los hombres un derecho de entrada más bajo que a las mujeres, y a la vez valoran a las candidatas que dan señales de su capacidad de jugar el juego y respetar las reglas de un modelo virilista que sigue siendo dominante dentro de la institución.

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)0.004
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.048
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.008
Scholarly communication0.0060.005
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0480.009

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 head0.096
GPT teacher head0.479
Teacher spread0.383 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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Same venueTravail genre et sociétésSame topicAging, Elder Care, and Social IssuesFrench-language works237,207