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Record W7080050640

Barriers and Strategies for Reducing Wait Times for Counselling in the Post-Pandemic Setting: Perspectives from Community-Based Sexual Assault Centres, and “This is a Societal Issue Not Just a Womxn's Issue”- Addressing the Impact of Vicarious Trauma in in Womxn-Dominated Nonprofit Gender-based Violence Services

2025· article· en· W7080050640 on OpenAlexaboutno aff

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2025
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisService providerService delivery frameworkDomestic violenceSexual violenceScapegoatingService (business)Sexual abusePoison control
DOInot available

Abstract

fetched live from OpenAlex

Barriers and Strategies for Reducing Wait Times for Counselling in the Post-Pandemic Crisis Setting: Perspectives from Community-Based Sexual Assault Centres The COVID-19 pandemic has intensified gender-based violence (GBV), placing unprecedented strain on nonprofit organizations already operating with limited resources. In Ontario, sexual assault services have increasingly relied on short-term, trauma-informed counselling strategies to manage rising demand and reduce waitlists. However, research has yet to comprehensively evaluate the benefits and limitations of these approaches within the nonprofit sector. This study addresses this gap by exploring perceptions of service delivery and short-term trauma-informed strategies used by service providers and advocating for increased funding to better support survivors. Grounded in critical feminist theory and a transformative paradigm, this research prioritizes intersectionality and inclusivity to enhance service accessibility and support within funding constraints. Semi-structured interviews with 8 service providers from 8 Ontario Coalition of Rape Crisis Centres (OCRCC) organizations informed a thematic analysis identifying key care practices and systemic barriers linked to underfunding. Findings contribute to more inclusive and sustainable support strategies, offering actionable recommendations for service providers and policymakers. By addressing funding challenges and promoting equitable practices, this research aims to strengthen the capacity of sexual violence nonprofits to support survivors in a post-pandemic crisis context. “This is a Societal Issue Not Just a Womxn's Issue”- Addressing the Impact of Vicarious Trauma in in Womxn-Dominated Nonprofit Gender-based Violence Services Vicarious trauma significantly impacts frontline workers, particularly in the nonprofit sector. In womxn-dominated gender-based violence organizations, where funding and resource constraints are common, the effects of vicarious trauma are especially severe yet under-researched (Shakespeare & Lafrenière, 2012). Using Bronfenbrenner's ecological approach with acritical feminist lens, this study explores how chronic underfunding in the nonprofit GBV sector exacerbates vicarious trauma among worker leading to the disempowerment of womxn. Semi-structured interviews were conducted with eight service providers from eight Ontario Coalition of Rape Crisis Centres (OCRCC) organizations, and content analysis was applied to identify key challenges. Findings reveal the perceptions of personal, organizational, and societal nature of GBV frontline work forces womxn to provide unpaid labor, reinforcing cycles of vicarious trauma that perpetuate GBV. This study underscores the urgent need for increased advocacy for structural support and funding to enable GBV service providers to offer care that recognizes and dismantles GBV. Recognizing GBV as a societal issue, not just a womxn's issue, this research calls for fair compensation and sustainable funding to ensure frontline workers have the resources necessary to provide effective care while safeguarding their own well-being as well as survivors.

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)0.009
metaresearch head score (Gemma)0.017
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 score0.262
Threshold uncertainty score0.521

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0140.009
Scholarly communication0.0080.005
Open science0.0030.007
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0070.000

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 head0.028
GPT teacher head0.282
Teacher spread0.254 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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