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Record W7133070274

The Geographic Context of 'Personal Responsibility': The Spatiality of Employment & Welfare Receipt among Unmarried Urban Women

2011· article· en· W7133070274 on OpenAlexaff
Timothy J. Haney

Bibliographic record

VenueTSpace · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsMount Royal University
Fundersnot available
KeywordsNeighbourhood (mathematics)ReceiptWelfarePunitive damagesContext (archaeology)Government (linguistics)Public policy
DOInot available

Abstract

fetched live from OpenAlex

Writers of the United States’ punitive 1996 welfare reform law assumed that women receiving government assistance transfers simply lacked motivation. This assumption ignores the myriad of individual and spatial barriers to employment that women face. Yet existing literature usually ignores the neighbourhoods in which women live. This research fills the gap by analyzing the extent to which both individual barriers to employment (health, childcare responsibilities, etc.) and neighbourhood characteristics are associated with employment and AFDC use just before welfare reform. Using data from the Multi-City Study of Urban Inequality, analyses indicate the significance of several neighbourhood-level, contextual barriers to employment. Results lend support to the role of health problems in preventing employment and increasing AFDC use, as well as several neighbourhood conditions including participant-observed disorder, neighbourhood joblessness, and the median age of neighbourhood structures. The paper concludes by discussing implications for social science theory, future research and public policy.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.095
GPT teacher head0.361
Teacher spread0.266 · 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
Published2011
Admission routes1
Has abstractyes

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