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Record W4384305564 · doi:10.36251/josi158

‘Where to now?’ Understanding the landscape of health and social services for homeless women in London, Ontario, Canada

2019· article· en· W4384305564 on OpenAlexaffabout
Amy Van Berkum, Abe Oudshoorn

Bibliographic record

VenueJournal of Social Inclusion · 2019
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsWestern University
Fundersnot available
KeywordsPhotovoiceThematic analysisAffordable housingParticipatory action researchSociologyGrounded theoryQualitative researchHousing FirstPublic relationsFeelingService providerGovernment (linguistics)Social workNursingMedicineMental healthPsychologyEconomic growthService (business)Political scienceBusinessSocial psychologySocial scienceMental illnessPsychiatry

Abstract

fetched live from OpenAlex

Homelessness is an ongoing social challenge effecting women in unique ways. The purpose of this research study was to understand a network of health and social services accessed by women experiencing homelessness, and how individuals successfully or unsuccessfully navigated these services. Data were collected utilizing a participatory application of the PhotoVoice method, grounded in a critical feminist intersectional perspective. Six women with lived experience of homelessness were recruited from a drop-in centre to participate in the six-week project. Through photo-taking, group discussions, arts-based dialogue, and individual interviews, themes were developed around women’s navigation of services and experiences of homelessness. A constant comparative method of thematic analysis was utilized so that themes could evolve iteratively and collaboratively with both the research team reflecting independently on qualitative data, and the women reflecting collaboratively on the data. Themes generated included: On the Margins; Feeling at Home; Mighty Women; Safety; Creating Home; and Whenever, Wherever. It is recommended that: 1) Communities keep developing more safe and affordable housing; 2) Government investments in homelessness include a general gender lens; 3) Women have access to 24-hour safe spaces; 4) Participatory research methodologies add valuable knowledge for women experiencing homelessness; and 5) Service providers be trained in trauma and violenceinformed care.

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 score0.464
Threshold uncertainty score1.000

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 studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.033
GPT teacher head0.355
Teacher spread0.321 · 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

Citations4
Published2019
Admission routes2
Has abstractyes

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