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Record W4385754531 · doi:10.1186/s12905-023-02541-7

“Our services are not the same”: the impact of the COVID-19 pandemic on care interactions in women’s shelters

2023· article· en· W4385754531 on OpenAlexafffund
Caitlin Burd, Isobel McLean, Jennifer C. D. MacGregor, Tara Mantler, Jill Veenendaal, C. Nadine Wathen

Bibliographic record

VenueBMC Women s Health · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversity of British ColumbiaWestern University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsWorkaroundPandemicContext (archaeology)Public relationsDistancingClosure (psychology)Health careCoronavirus disease 2019 (COVID-19)Work (physics)Political scienceNursingBusinessPsychologyMedicineGeography

Abstract

fetched live from OpenAlex

BACKGROUND: Guidelines and regulations in response to the COVID-19 pandemic have significantly impacted the health care sector. We explore these impacts in the gender-based violence (GBV) services sector and, more specifically, in the context of women's shelters. METHODS: Using an interpretive description and integrated knowledge mobilization approach, we interviewed 8 women's shelter clients, 26 staff, and conducted focus groups with 24 Executive Directors. RESULTS: We found that pandemic responses challenged longstanding values that guide work in women's shelters, specifically feminist and anti-oppressive practices. Physical distancing, masking, and closure of communal spaces intended to slow or stop the spread of the novel coronavirus created barriers to the provision of care, made it difficult to maintain or create positive connections with and among women and children, and re-traumatized some women and children. Despite these challenges, staff and leaders were creative in their attempts to provide quality care, though these efforts, including workarounds, were not without their own challenges. CONCLUSIONS: This research highlights the need to tailor crisis response to sector-specific realities that support service values and standards of 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.115
GPT teacher head0.451
Teacher spread0.336 · 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 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

Citations13
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueBMC Women s HealthSame topicIntimate Partner and Family ViolenceFrench-language works237,207