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Record W2087492694 · doi:10.1300/j005v35n02_07

Community Service Providers' Conceptualizations of the Needs and Services of Depressed Rural Women

2008· article· en· W2087492694 on OpenAlexaffabout
Mandy York, Péter Horváth

Bibliographic record

VenueJournal of Prevention & Intervention in the Community · 2008
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsAcadia UniversityUniversity of Alberta
Fundersnot available
KeywordsService providerNova scotiaRural communityService (business)Depression (economics)Qualitative researchRural areaPublic relationsCommunity serviceNursingPsychologyBusinessMedicinePolitical scienceSociologySocioeconomicsMarketing

Abstract

fetched live from OpenAlex

Representatives from community and volunteer organizations (N = 37) in a rural region of Nova Scotia were interviewed on their views of the causes, prevention and treatment of depression in rural women. Utilizing a qualitative analysis, five themes were identified in their responses: the needs and stresses of women with depression; the problems of women in rural areas; obstacles and barriers to accessing services; the inadequacy of treatment services; and recommendations for improving prevention and treatment. The findings suggested that community service providers were consistent in their views of the needs and stresses of depressed women in rural areas and the kinds of services that would remedy them. Making community service providers aware of the consistencies in their views may promote more inter-agency cooperation and the development of community-centered approaches to the treatment of depression in rural women.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.114
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.098
GPT teacher head0.408
Teacher spread0.310 · 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

Citations1
Published2008
Admission routes2
Has abstractyes

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