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Record W7096013135

Canadian Journal of Counselling / Revue canadienne de counseling/2006, Vol. 40:4 209 Alliance Skill Development within Canadian First Nations and Aboriginal Counsellor Education

2016· article· en· W7096013135 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsnot available
Fundersnot available
KeywordsAlliancePlan (archaeology)Foundation (evidence)Process (computing)
DOInot available

Abstract

fetched live from OpenAlex

Although a focus on counsellor-client alliance is prominent within counsellor education, specifi c skills that compose this aspect of the helping process remain nebulous. As such, faculty and students have relied on general guidelines and suggestions regarding the engagement process. Research conducted by Bedi, Davis, and Arvay (2005), however, has been instrumental in reversing this trend and provides an excellent foundation with which to better understand elements essential to the alliance process. This article discusses these fi ndings in relation to Canadian First Nations and Aboriginal (FNA) counsellor education and emphasizes cultural imperatives and practices. résumé Bien qu’une concentration sur l’alliance entre le conseiller et le client fi gure au premier plan dans la formation des conseillers, les compétences précises dont cet aspect du pro-cessus d’aide est composé demeurent nébuleuses. À ce titre, les professeurs et les étudi-ants se sont fi és aux lignes directrices et suggestions générales concernant le processus d’engagement. Des recherches menées par Bedi, Davis, et Arvay (2005) ont toutefois

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)0.003
metaresearch head score (Gemma)0.007
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: none
Teacher disagreement score0.150
Threshold uncertainty score0.302

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0120.008
Scholarly communication0.0060.002
Open science0.0020.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0570.004

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 head0.008
GPT teacher head0.200
Teacher spread0.192 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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