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Record W2270603304 · doi:10.24135/nzjc.v29i1.107

Activities Influencing the Professional Development of New Zealand Counsellors Across Their Careers.

2009· article· en· W2270603304 on OpenAlexaboutno aff
Nikolaos Kazantzis, Sarah Calvert, David E. Orlinsky, Sally E. Rooke, Kevin R. Ronan, Paul L. Merrick

Bibliographic record

VenueNew Zealand Journal of Counselling · 2009
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsnot available
Fundersnot available
KeywordsProfessional developmentCareer developmentMedical educationBusinessPublic relationsPolitical scienceMedicine

Abstract

fetched live from OpenAlex

New Zealand counsellors (n = 123) were surveyed as an extension of a multinational study of therapist development. Comparisons were made with samples of Canadian and US counsellors. New Zealand counsellors perceived themselves to have developed in skill and knowledge across their careers, and reported high levels of ongoing development at all stages of their careers. Involvement in supervision and training were notably high, exceeding that of the Canadian and US samples, and did not diminish with increasing time in practice. Involvement in personal therapy was also high, though slightly lower than the comparison samples. New Zealand counsellors regarded supervision, training, and personal therapy as having had a strong, positive influence on their professional development. Ratings of the influence of these activities exceeded the ratings of comparison samples. [ABSTRACT FROM AUTHOR] Copyright of New Zealand Journal of Counselling is the property of New Zealand Association of Counsellors and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.904
Threshold uncertainty score0.678

Codex and Gemma teacher scores by category

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

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 head0.032
GPT teacher head0.330
Teacher spread0.299 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2009
Admission routes1
Has abstractyes

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