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Record W4384376623 · doi:10.36251/josi166

Social inclusion for women experiencing homelessness

2020· article· en· W4384376623 on OpenAlexaff
Jenna Richards, Abe Oudshoorn, Laura Misener

Bibliographic record

VenueJournal of Social Inclusion · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsWestern University
Fundersnot available
KeywordsInclusion (mineral)Social exclusionThematic analysisPovertySociologyQualitative researchGovernment (linguistics)Gender studiesPsychologyPolitical scienceSocial science

Abstract

fetched live from OpenAlex

Background: People experiencing homelessness have been described as one of the most socially excluded groups (Everett 2009; Labonte, 2004), particularly homeless women (Wesely & Wright, 2005). Exploring the barriers and facilitators to social inclusion for women experiencing homelessness, in addition to their experience of sports, may provide the information required to increase their access to community activities and result in increased inclusion. 
 Methods: Qualitative thematic analysis was used to explore women’s homelessness, social inclusion, and sports. Data was collected using semi-structured interviews with eleven women residing in a shelter. The data were analyzed for themes relating to the research questions. 
 Findings: Four themes are proposed from the interviews: (a) poverty is exclusion, (b) housing is not (necessarily) a prerequisite for social inclusion, (c) women play sports, and (d) it’s just a piece of paper. These themes represent the barriers and facilitators of social inclusion that the participants experienced, as well as their experiences and interests in sports.
 Conclusion: The findings revealed that while women may be interested in sports as an opportunity to experience inclusion, they faced many barriers in accessing sports as a service for people experiencing homelessness. The findings of this study may inform organizational and government policy, and future research. Further intersectional research is needed to understand how gendered experiences of homelessness intersects for Indigenous or racialized persons. 

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0120.000
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.071
GPT teacher head0.432
Teacher spread0.360 · 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 teacher head, not a consensus.

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

Citations1
Published2020
Admission routes1
Has abstractyes

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