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An Investigation of Tasks and Techniques Associated With Dynamic Interview Adequacy

2005· article· en· W1977314816 on OpenAlexaff
J. Christopher Perry, J. Christopher Fowler, Trent Semeniuk

Bibliographic record

VenueThe Journal of Nervous and Mental Disease · 2005
Typearticle
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsInterviewPsychological interventionPsychologyDynamic assessmentApplied psychologyClinical psychologyAffect (linguistics)Exploratory researchIntervention (counseling)Semi-structured interviewSocial psychologyQualitative researchDevelopmental psychologyPsychiatryCommunication

Abstract

fetched live from OpenAlex

We examined the hypotheses that adequately conducted dynamic interviews would be associated with performance on five interview tasks, which, in turn, would be associated with specific clinical techniques. Ten subjects provided two dynamic interviews each, one rated higher and one lower in overall dynamic adequacy. Interviews were independently rated for completion of five interviewer tasks. Another rater independently categorized each therapist intervention as one of 10 therapeutic interventions. Dynamic interview adequacy was associated with four of five interview tasks, attributable to the interviewer's contribution, after controlling for the subject's contribution. Four tasks-frame setting, exploration of affect, interpretation, and synthesis-were associated with specific clinical interventions, whereas offering support was not. The overall thoroughness of completing the interview tasks was highly associated with dynamic adequacy and the ratio of exploratory to supportive interventions. The adequately conducted dynamic interview is associated with identifiable tasks and techniques that should facilitate teaching it for research or clinical use.

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)0.086
metaresearch head score (Gemma)0.508
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.455

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0860.508
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.002
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.361
Teacher spread0.332 · 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 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

Citations32
Published2005
Admission routes1
Has abstractyes

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