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Record W7100784621

Training problem gambling counsellors in Congruence Couple Therapy: Evaluation of training outcomes. International Gambling Studies, 8(1), 95–111. Available from http://hdl.handle.net/10133/567 This article was accessed from from the

2008· article· en· W7100784621 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Maritime and Colonial Histories
Canadian institutionsnot available
Fundersnot available
KeywordsCongruence (geometry)Training (meteorology)TeleconferenceQualitative researchSample (material)
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACT Congruence Couple Therapy (CCT) is an integrative, humanistic, systemic model for problem gambling treatment. This study evaluates the efficacy of CCT training in imparting key concepts, skills and values of CCT to a sample of problem gambling counsellors (N = 21) from 13 Ontario problem gambling treatment programmes. CCT training comprised of a 4-day residential workshop followed by 12 weeks of CCT application to couples supported by teleconference consultation. Two cycles of training were conducted. The evaluations were driven by two controlled designs using quantitative measures complemented by qualitative data. Triangulated mixed methods findings indicate that counsellors increased significantly their knowledge of CCT concepts, values and skills from both training cycles. Trainee satisfaction was highly positive. Further studies on CCT and CCT training are recommended in light of these results.

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)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.212
GPT teacher head0.375
Teacher spread0.163 · 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 designObservational
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

Citations0
Published2008
Admission routes1
Has abstractyes

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