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Record W3125761749 · doi:10.1186/s12905-020-01170-8

Exploring the impact of a community participatory intervention on women's capability: a qualitative study in Gulu Northern Uganda

2021· article· en· W3125761749 on OpenAlexafffund
Loubna Belaid, Emmanuel Ochola, Pontius Bayo, George William Alii, Martin Ogwang, Donato Greco, Christina Zarowsky

Bibliographic record

VenueBMC Women s Health · 2021
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsUniversité de MontréalMcGill University
FundersCanadian Institutes of Health ResearchGlobal Affairs CanadaInternational Development Research Centre
KeywordsFocus groupThematic analysisPsychological interventionParticipatory action researchQualitative researchCitizen journalismInequalityPsychologyIntervention (counseling)Domestic violenceSociologyNursingPolitical sciencePoison controlMedicineSuicide preventionEnvironmental healthSocial science

Abstract

fetched live from OpenAlex

BACKGROUND: Community participatory interventions mobilizing women of childbearing age are an effective strategy to promote maternal and child health. In 2017, we implemented this strategy in Gulu Northern Uganda. This study explored the perceived impact of this approach on women's capability. METHODS: We conducted a qualitative study based on three data collection methods: 14 in-depth individual interviews with participating women of childbearing age, five focus group discussions with female facilitators, and document analysis. We used the Sen capability approach as a conceptual framework and undertook a thematic analysis. RESULTS: Women adopted safe and healthy behaviors for themselves and their children. They were also able to respond to some of their family's financial needs. They reported a reduction in domestic violence and in mistreatment towards their children. The facilitators perceived improved communication skills, networking, self-confidence, and an increase in their social status. Nevertheless, the women still faced unfreedoms that deprived them of living the life they wanted to lead. These unfreedoms are related to their lack of access to economic opportunities and socio-cultural norms underlying gender inequalities. CONCLUSION: To expand women's freedoms, we need more collective political actions to tackle gender inequalities and need to question the values underlying women's social status.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.249
GPT teacher head0.460
Teacher spread0.211 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations16
Published2021
Admission routes2
Has abstractyes

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