Advocating for Ourselves, Advocating for Our Communities: Canadian Counselling Psychology Into the Next Decade and Beyond
Bibliographic record
Abstract
This special issue of Canadian Journal of Counselling and Psychotherapy is an outgrowth of the landmark 2018 Canadian Counselling Psychology Conference called “Advocating for Ourselves, Advocating for Our Communities: Canadian Counselling Psychology Into the Next Decade and Beyond.” This conference centred on seven working groups: the future of counselling psychology education and training in Canada, foregrounding clinical practice and clinical supervision within the field of Canadian counselling psychology, student advocacy in Canadian counselling psychology, responding to the TRC in Canadian counselling psychology, internationalization of counselling psychology, the role of Canadian counselling psychology in advocating for the needs of members of under-represented groups, and the responsibility of Canadian counselling psychology to reach systems, organizations, and policy-makers. This introduction highlights the seven articles included in this special issue, each of which summarizes the discussion included within one working group and elaborates upon topics that emerged within each working group discussion. We expect that, after reading the articles contained within this special issue, readers will be able to experience some of the intellectual stimulation and inspiration felt by many who attended the working groups in person. We also hope that this collection of articles will inspire those who did not attend the conference to advocate for and to help increase the presence and the influence of Canadian counselling psychology locally, provincially, nationally, and globally as it seeks to promote the best interests of the various communities it serves.
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 | 0.013 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.029 | 0.015 |
| Scholarly communication | 0.024 | 0.010 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".