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Record W2082953470 · doi:10.1080/j003v20n03_04

Occupational Concerns of Women Who Are Homeless and Have Children: An Occupational Justice Critique

2006· article· en· W2082953470 on OpenAlexaboutno aff
Betsy VanLeit, Rebecca Starrett, Terry K. Crowe

Bibliographic record

VenueOccupational Therapy In Health Care · 2006
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational therapyEmpowermentInjusticeExploratory researchPsychologyOccupational scienceOccupational prestigeMedicineSocioeconomic statusSocial psychologyEnvironmental healthPsychiatrySociologyPolitical scienceSocial sciencePopulation

Abstract

fetched live from OpenAlex

SUMMARY The purpose of this exploratory study was to describe the occupational goals and concerns of women who are homeless with children. Twenty-seven women with children living in homeless shelters completed interviews using the Canadian Occupational Performance Measure (COPM). Occupational issues and concerns were identified for each participant, and then they were pooled. A total of 169 occupational concerns were described and analyzed. The most common occupational issues identified by participants concerned finances, employment, education, transportation, housing, time for self, personal appearance, home management, and parenting. Analysis of identified occupational concerns suggests that the homeless women with children experienced a range of institutional and social barriers to occupational participation: essentially a form of occupational injustice. This study raises questions concerning the most effective roles for occupational therapists to facilitate empowerment so that women who are homeless may fully participate in the communities where they live.

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)0.006
metaresearch head score (Gemma)0.012
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 score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.016
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0020.003
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 head0.097
GPT teacher head0.500
Teacher spread0.403 · 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

Citations21
Published2006
Admission routes1
Has abstractyes

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