Bibliographic record
Abstract
This comparative study explored differences in perceptions between Canadian and US post secondary faculty in the fields of adult education (AdEd) and human resource development (HRD) on program development issues in the emerging field of “workplace learning”. In fall of 2001, The Adult Education and Human Resource Development Faculty Survey was electronically disseminated to a selected sample of Canadian and US faculty across both countries. The authors examine respondents' perceptions of: their program's curricular focus on the individual students' learning needs compared to the organization development goals of their current or potential employers; the importance of specific skills to the role of “workplace learning practitioner” compared to skill building opportunities present in the program; and the degree of cooperation between their academic programs and businesses that employs, or potentially employs, graduates from these programs. The findings reveal differences in the manner in which Canadian and US faculties develop and teach in these programs that the authors believe have important implications for the continuing development of this field of inquiry and practice in both countries. Overall, the study argues for closer and more purposeful collaboration between AdEd and HRD faculties who develop and teach in workplace learning programs in both countries, and highlights the importance of alliance building on several fronts in order for this newly emerging field of practice and inquiry to flourish.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.016 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".