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Record W2908980809 · doi:10.60770/ztg8-g079

Availability and accessibility of community based services for family violence victims: a comparative case study of Trochu, Alberta and Calgary, Alberta

2017· dissertation· en· W2908980809 on OpenAlexaffabout
Camille Cunningham

Bibliographic record

VenueMount Royal University Institutional Repository (Mount Royal University) · 2017
Typedissertation
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsMount Royal University
Fundersnot available
KeywordsDomestic violenceGeographyCriminologyPolitical scienceEnvironmental healthPsychologyMedicineHuman factors and ergonomicsPoison control

Abstract

fetched live from OpenAlex

Using a comparison case study method, the goal of this undergraduate honours project was to compile a resource inventory of the community based services for victims of family violence specific to a Southern Alberta rural town to those in an urban area. This topic is important to examine because rates of family violence are higher among rural populations than in urban areas (Statistics Canada, 2016, p. 43; Northcott, 2011, p. 10). Due to the unique nature of family violence criminality and victimization, victims require additional supports beyond those provided by the criminal justice system. Community based agencies offer various resources that may be used in helping individuals cope with, address, and/or escape situations involving family violence. The resource inventory includes and compares the community based services available to victims of family violence in the rural community of Trochu, Alberta, to those available in the urban center of Calgary, Alberta. In short, while there was no difference in the community based services available to family violence victims, differences were in the accessibility of community services were apparent in terms of: geography and transportation options; diversity of services; and the technology used by the agencies.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0070.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.041
GPT teacher head0.336
Teacher spread0.295 · 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 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
Published2017
Admission routes2
Has abstractyes

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