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Record W4239325349 · doi:10.4324/9781351200752

Conversation Analysis for Social Work

2018· book· en· W4239325349 on OpenAlexaff
Gerald A. J. de Montigny

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsCarleton University
Fundersnot available
KeywordsConversationWork (physics)Conversation analysisSociologyPsychologyCommunicationEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

What do the stories youth in state care tell about life in their family of origin? What stories do they tell us about coming into care, living in care, and relationships with foster-parents and social workers? This book presents the stories of youth in care, though not in splendid isolation, but as interactively produced, turn by turn in interviews, and in conversations with other youth. By using tools from conversation analysis (CA), the author examines interviews with youth in care and social workers, to unfold the essential and incorrigible reflexivity of story production. CA allows us to grasp the ways that a youth’s story emerges turn by turn, and is an artefact of a social relation between a youth and an interviewer. This text provides social work readers with a sense of art, artistry, and ambiguity at the heart of social interaction. It will be required reading for all social work students and academics looking for a deeper, more philosophical understanding of the profession.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.219
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0310.001

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 head0.080
GPT teacher head0.403
Teacher spread0.323 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2018
Admission routes1
Has abstractyes

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