MétaCan
Menu
Back to cohort
Record W1826361587 · doi:10.61611/2165-4611.1083

The Development of Dual and Multiple Relationships for Social Workers in Rural Communities

2015· article· en· W1826361587 on OpenAlexafffundabout
Tammy Piché, Keith Brownlee, Glenn Halverson

Bibliographic record

VenueContemporary Rural Social Work Journal · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsUniversity of CalgaryLakehead University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCLARITYDual (grammatical number)Mental healthSocial workPsychologyEmpirical researchSocial psychologyPublic relationsPolitical science

Abstract

fetched live from OpenAlex

Mental health professionals who work in small, rural communities often have to contend with dual and multiple relationships. The more integrated service providers are within the community, the more likely they will encounter overlapping personal and professional relationships with clients. Although there is extensive literature on the potential risks of dual and multiple relationships, little empirical evidence exists which addresses the contextual factors that specifically lead to these relationships in rural social work practice. This qualitative study explored the experiences of twelve social workers or social service workers practicing in northern and northwestern Ontario. Findings provide some insight into the complexity and dynamics of dual and multiple relationships in small towns, as well as worker perspectives on the specific contextual circumstances that result in mental health workers encountering these relationships. The unique contribution of this paper to the literature is to highlight factors that increase the likelihood of dual and multiple relationships when they are not as obvious as a clear and immediate conflict of interest. Greater clarity about such precipitating factors will contribute to supervision, training, and sound policy development informed by contextual sensitivity.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0090.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.227
GPT teacher head0.380
Teacher spread0.152 · 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

Citations5
Published2015
Admission routes3
Has abstractyes

Explore more

Same venueContemporary Rural Social Work JournalSame topicSocial Work Education and PracticeFrench-language works237,207