Co‐op students' access to shared knowledge in science‐rich workplaces
Bibliographic record
Abstract
Abstract Wenger's (1998) concepts “community of practice,” “brokering,” and “transfer” explain the challenges co‐operative (co‐op) education students face in relating the knowledge learned in school with what they learn while participating as members of a workplace. The research for this paper is set within the contexts of the knowledge economy and increased collaboration in the workplace. The paper draws on several qualitative studies of work‐based education to examine the similarities and differences between learning in the workplace and learning in school, with a focus on science education and science‐rich workplaces. Barriers to connecting school knowledge and workplace knowledge include the nature of science (its purpose, accountability, and substance), the structure of knowledge in each setting, the form content knowledge takes, the sequence that the curriculum is presented in, and the gatekeeping that occurs when knowledge is accessed. The paper addresses implications for interventions in school and the workplace, with attention to the transition from school to work, and concludes by pointing to profound obstacles to connecting school knowledge with workplace knowledge. © 2006 Wiley Periodicals, Inc. Sci Ed 91:115–132, 2007
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".