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Record W4281777757 · doi:10.1111/phn.13096

Creating safe relational space: Public health nurses work with mothering refugee women

2022· article· en· W4281777757 on OpenAlexaffabout
Shahin Kassam, Lenora Marcellus

Bibliographic record

VenuePublic Health Nursing · 2022
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsRefugeePublic healthPublic health nursingIntersectionalityNursingSociologyPopulationPsychologyPublic relationsGender studiesMedicinePolitical science

Abstract

fetched live from OpenAlex

OBJECTIVE: Exploring how public health nurses (PHNs) provide community-based support to women who are refugees and mothering. DESIGN: A constructivist grounded theory (CGT) design was used where intersectionality as an analytical tool was applied. Varying data collection approaches including focus groups were used. SAMPLE: Twelve PHNs from four public health units in Western Canada participated in this study. RESULTS: Participants in this study described an overall process of creating safe relational space to address a basic social problem of establishing trust while managing structural forces. This overarching process was expressed through burning with passion, connecting while looking beyond, protecting from re-traumatization, and fostering independence. Findings reveal strategies PHNs used to enhance health equity. This study extends critical caring theory to include sociopolitical and economic influences on public health nursing practice. Consequences of these influences on the mothering refugee women population are also revealed. Implications include structural integration of trauma-and-violence-informed principles to support public health nursing practice. CONCLUSIONS: This study adds to an emerging body of knowledge on PHNs work with complex populations. Innovative application of intersectionality is demonstrated as an effective approach to analyzing impacts of broad sociopolitical priorities on communities that are systemically marginalized.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.063
GPT teacher head0.359
Teacher spread0.297 · 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 designNot applicable
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

Citations8
Published2022
Admission routes2
Has abstractyes

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