Bibliographic record
Abstract
Polytechnic institutions are ideal partners for disruption and transformation.They offer industry-relevant programs, equipment and facilities that prepare learners for the workplace, support mid-career workers updating their skills and help solve real-world innovation and productivity challenges.In May of 2019, Polytechnics Canada hosted its Annual Showcase at the Kwantlen Polytechnic University campus, to share the results of a brainstorming session that began with the question, How are polytechnics disrupting post-secondary education in Canada?The result was a program that reflected diverse and innovative initiatives across campuses: cultural shifts, reimagined classrooms and curricula, light-filled innovation spaces and business partnerships all designed to prepare today's learners for tomorrow's workplaces.Included in this special issue of JIPE are abstracts from four of those presentations, as well as insights provided by our two keynotes, to provide a glimpse of the innovative ideas discussed.Join us on May 13-14, 2020 at Fanshawe College in London, Ontario, for further discussions -this time on Know-how partners for a knowledge economy.Keep an eye on www.polytechnicscanada.ca for more information.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.524 | 0.538 |
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".