Bibliographic record
Abstract
The innovation achievements and momentum of the COVID-19 pandemic present an opportunity for Canadian polytechnics to sustain their unique and distinctive role in the post-secondary landscape. The authors contend that if polytechnics collaborate with workplace partners to research and to advance Employee-led Workplace Innovation capabilities, polytechnics can better equip learners for the future of work, foster innovation in the workplaces of partners, and contribute meaningfully to innovation-based growth in Canada. Drawing on Breznitz’ critique, the authors advance the idea that Canadian innovation will grow if it focuses on ‘agents of innovation’, specifically the individual. Then the paper briefly outlines the traits of individual ‘serial innovators’ before honing in on the research and the work underway globally in the area of Employee-led Workplace Innovation. After establishing its value, the authors contend that if the work of polytechnics is to continue to have relevance for industry and to be differentiated from other types of post-secondary institutions, then the integration of Employee-led Workplace Innovation can play a key role. Its successful integration, however, requires an epistemological shift from the status quo, a shift which is described by way of a historical analogue and an example of curricular implications. The authors then explore the opportunity to build instructional capability for innovation in polytechnics themselves, both as a way to improve learning and as topic in its own right. Finally, the paper concludes with a summary of the opportunity polytechnics now have to sustain and possibly to evolve their unique role in strategic workforce development.
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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.023 |
| Scholarly communication | 0.024 | 0.013 |
| Open science | 0.002 | 0.026 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".