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Women and Health: In the Context of Global Restructuring

2009· article· en· W1950752764 on OpenAlexvenueno aff
Shanzida Farhana

Bibliographic record

VenueCanadian social science · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsRestructuringPovertyPolitical scienceInequalityContext (archaeology)Health careGlobal healthHumanitiesDevelopment economicsEconomic growthGeographyEconomicsArt

Abstract

fetched live from OpenAlex

Recently there is a debate about the impact of global restructuring on human health. this article will attempt to examine the impact of global restructuring on the health of poor women in a range of different setting. It will also give a brief account of gender inequalities in access to health care and recent campaigns designed to resist the negative changes. Key words: global restructuring, women’s health, gender inequality, poverty, well-being Resume: Recemment, il y a un debat sur l'impact de la restructuration mondiale sur la sante humaine. cet article tentera d'examiner l'impact de la restructuration mondiale sur la sante des femmes pauvres dans une gamme de circonstances differentes. Il donnera aussi un bref compte rendu des inegalites entre les sexes dans l'acces aux soins de sante et les recentes campagnes designees a resister aux changements negatifs. Mots-Cles: restructuration mondiale, sante des femmes, inegalite entre les sexes, pauvrete, bien-etre

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)0.004
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: none
Teacher disagreement score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.023
Scholarly communication0.0070.004
Open science0.0010.006
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.039
GPT teacher head0.319
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
Published2009
Admission routes1
Has abstractyes

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