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Record W2585196713

Kinship Care Policy: Women's Oppression & Neoliberal Familialization

2013· book· en· W2585196713 on OpenAlexaboutno aff
Martha Susana Lara

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicResearch in Social Sciences
Canadian institutionsnot available
Fundersnot available
KeywordsOppressionPovertyWelfare reformSocial policyNeoliberalism (international relations)KinshipContext (archaeology)Welfare stateState (computer science)Single mothersWelfarePolitical scienceEconomic growthPolitical economySociologyDevelopment economicsEconomicsPoliticsLawGeography
DOInot available

Abstract

fetched live from OpenAlex

Under neoliberal capitalist globalization, the deepening of women’s oppression and exploitation have been notorious. Indeed, women are facing poverty all over the world, including in industrialized capitalist countries. Women living in poverty and particularly poor single mothers have been targets of the counter neoliberal reform of the capitalist welfare state. This counter reform is a gendered, classist, and complex alteration that has assaulted the social responsibilities and budgets of the welfare state. In Ontario, Neoliberal policies reinforce women’s unpaid caring responsibilities and intensify the surveillance and control exerted over poor Ontarian single mothers. This qualitative case study has explored critically the role of neoliberal social policy in Ontario child welfare. Through a feminist approach and using official documentary data, the research analyzes Ontario Kinship Care Policy. The study looks at the historical and social context in which the policy was formulated, depicts the main goals of the policy, and analyzes the policy’s outcomes both, for the system and for women. Possible areas of future research on this policy are presented in the conclusions.

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)0.002
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 score0.828
Threshold uncertainty score0.527

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.017
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.032
GPT teacher head0.374
Teacher spread0.342 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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Same topicResearch in Social SciencesFrench-language works237,207