A process-oriented approach to learning process-oriented counselling skills in groups. Canadian
Bibliographic record
Abstract
This article describes the teaching of process-oriented counselling skills in a group. The interweaving of theory and practice is discussed. The need for and a method of inte-grating the personal and professional growth of group members with the experiential and conceptual learning of counselling skills are outlined. The congruence of the con-tent and the educational approach is an important element in the training. The devel-opment and significance of the community of learners, an intrinsic dimension of the training, are also described. Cet article décrit l’enseignement en groupe de compétences de counseling axées sur le processus. On y discute de la façon dont la théorie et la pratique s’entremêlent. On y trace par ailleurs les grandes lignes du besoin d’intégrer la croissance personnelle et professionnelle des membres du groupe à l’apprentissage expérientiel et conceptuel des compétences en counseling, et de la méthode pour y arriver. La congruence entre le contenu et l’approche pédagogiques est un élément important de cette formation. La croissance et l’importance de la communauté des apprenants font partie intrinsèque du programme et sont aussi décrits.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".