Bibliographic record
Abstract
Well-documented changes in the world of work have increased exponentially the importance of career guidance services. The career guidance field has taken up the challenges of renewed training of professionals, invigorated practices in relation to education programs, counselling and information, and engaged in extended and sustained thinking on the responses of the field to the changes. The career guidance field has been expanding the focus of its interventions and stressing the need to examine its development to date and the most appropriate directions for the future. For example, the International Association for Educational and Vocational Guidance conducted a conference in 1996 on the changing demands of career guidance and, in 2000, embarked on the development of a new journal. In 1999, a major international symposium held in Canada focused on career development and public policy (Hiebert & Bezanson, 1999), with work ongoing in 2001. New editions of major theoretical texts have been developed (Brown & Brooks, 1996; Osipow & Fitzgerald, 1996) and new texts featuring new theoretical formulations and the interplay between theory and practice also have been published (Patton & McMahon, 1999; Savickas & Walsh, 1996).
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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.
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".