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Record W615314750 · doi:10.2307/25149523

Safe Haven: The Story of a Shelter for Homeless Women

2004· article· en· W615314750 on OpenAlexvenueno aff
Nancy Janoviček, Rae Bridgman

Bibliographic record

VenueLabour / Le Travail · 2004
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsSafe havenHavenArtPsychologySociologyGender studiesEconomics

Abstract

fetched live from OpenAlex

In this groundbreaking work, urban anthropologist Rae Bridgman, in careful and intimate detail, explores the perspectives of the women who work and live at Savard's, a unique shelter for homeless women. Bridgman uses the design and development of Savard's - a housing model developed by women for women - as an opportunity to document the project's original vision and what happened once it opened. There are few rules at Savard's. Women may come and go as they wish, and referrals to other services are made only when a woman has indicated interest in taking action on her own behalf. It is a model that aims to provide a safe haven for the chronically homeless. The study traces the evolution of this type of shelter, providing qualitative research and useful analysis for academics, policy-makers, service providers, and activists. Based on many hours of participant observation as well as interviews and staff records, Safe Haven presents a distinct picture of the chronically homeless and those on the frontlines of this lifesaving service.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.034
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0340.025
Scholarly communication0.0070.007
Open science0.0020.011
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0050.001

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 head0.031
GPT teacher head0.344
Teacher spread0.314 · 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

Citations14
Published2004
Admission routes1
Has abstractyes

Explore more

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