MétaCan
Menu
← Back to cohort
Record W186359707 · doi:10.12794/metadc115170

Improving Family-provider Relationships Through Cultural Training and Open-ended Client Interviews

2012· dissertation· en· W186359707 on OpenAlexaff
Megan J. Thompson

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsGlobal Affairs Canada
Fundersnot available
KeywordsPsychologySocial psychologyKnowledge managementComputer science

Abstract

fetched live from OpenAlex

Behavior analysts form parent-professional relationships with families of many different backgrounds. the study evaluated the effectiveness of a training program to teach behavior analysts to utilize an open family interview format. the study was conducted at an autism treatment program. a pre-post treatment design with in vivo simulation probes before and after training was used to assess the effects of the workshop on the participants and parents’ verbal behavior. Results showed that rate of questions per minute and number of closed-ended questions decreased after training, the duration of interviews decreased after training, the number of closed-ended questions significantly decreased after training, and frequency of the discussion topic of child goals increased after training. in general, interviewer responses varied. Preliminary data and parent questionnaire responses suggested parents were comfortable with the new interview format and felt the behavior analyst understood cultural and family needs.

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)0.035
metaresearch head score (Gemma)0.077
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 score0.035
Threshold uncertainty score0.187

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.077
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0010.003
Open science0.0030.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.304
GPT teacher head0.450
Teacher spread0.145 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

Explore more

Same topicFamily and Disability Support Research→French-language works237,207→