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Record W4283217912 · doi:10.1093/bjsw/bcac113

Supervision of Information Communication Technologies in Social Work Practice: A Mixed Methods Study

2022· article· en· W4283217912 on OpenAlexafffundabout
Karen M. Sewell, Faye Mishna, Jane E. Sanders, Marion Bogo, Betsy Milne, Andrea Greenblatt

Bibliographic record

VenueThe British Journal of Social Work · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsThe King's UniversityWestern UniversityUniversity of TorontoCarleton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsInformation and Communications TechnologyThematic analysisReflexivitySupervisorPsychologyICTSSocial workData collectionQualitative researchWork (physics)Qualitative propertyPublic relationsKnowledge managementApplied psychologySociologyManagementPolitical scienceEngineeringComputer science

Abstract

fetched live from OpenAlex

Abstract The integration of informal information and communication technologies (ICTs) has transformed social work practice, yet the use of ICTs in practice is not commonly discussed in supervision. The aim of this sequential mixed methods study was to understand the factors associated with social workers’ discussion of informal ICT use in supervision, and the considerations that influence these discussions. A logistic regression was conducted using data from Canadian #socialwork survey participants in organisational settings (n = 958). Quantitative findings were integrated with the qualitative findings from a reflexive thematic analysis of participant interviews (n = 22), some of which occurred during and were impacted by the COVID-19 pandemic. Based on our integrated findings, supervisory ICT discussion was highly dependent on organisational policy and supervisors’ interpretation of these policies. The setting in which the survey participants worked was also associated with ICT discussion in supervision. In making their decisions to discuss ICT use, interview participants further highlighted the importance of the supervisory relationship based on supervisor qualities and availability.

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)0.016
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.651
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.005
Science and technology studies0.0100.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.040
GPT teacher head0.417
Teacher spread0.377 · 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

Citations3
Published2022
Admission routes3
Has abstractyes

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