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Record W4253901161 · doi:10.32920/ryerson.14654835

The Impact of Violence and Acknowledgement of Trauma on the Mental Health of Black Canadians

2021· preprint· en· W4253901161 on OpenAlexaff
Karia Jones

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsToronto Metropolitan UniversityCentre for Social Innovation
Fundersnot available
KeywordsAcknowledgementMental healthStigma (botany)Grounded theorySymbolic interactionismNarrativeSociologyPsychological resilienceSocial psychologyPsychologyCriminologyGender studiesQualitative researchSocial sciencePsychotherapistPsychiatryComputer security

Abstract

fetched live from OpenAlex

This research paper will explore the foci surrounding the Black community, particularly on violence and mental health, through a literature review of existing studies. The goal of this research is to create space for narratives that will encourage and enable participants to talk in new and potentially transgressive ways. Grounded theory used to ground the finding in the research while symbolic interactionism and Critical race theory were utilized as theoretical lens. This MRP demonstrates the various forms of violence, mental health stigma and hesitancy to access services, and resilience within Black individuals Thus, more research and programs need to be developed in order to be able to understand the diverse levels of violence the Black community faces and how to limit the barriers they face internally and externally in regard to outside assistance.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.272

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0170.004
Scholarly communication0.0050.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.036
GPT teacher head0.416
Teacher spread0.380 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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