The price of admission: Examining how expectancies and values can overcome innovation
Bibliographic record
Abstract
This study examines the expectancies, values, and costs that are involved in motivating current Canadian innovators. While much of the innovation literature is dominated by studies from the business literature, this study adopts an interdisciplinary approach that expands the scope of innovation to reflect a more diverse perspective encompassing radical and incremental innovators that generate social and/or economic wealth. Through the lens of Expectancy-Value Theory, this study will ask existing Canadian innovators about their experiences and perceptions of innovation to identify their implicitly and explicitly held motivations through interviews. 15-20 existing Canadian innovators selected from a variety of disciplines including engineering, business, design, scholastics, and artists will inform the development and administration of an inventory administered to 500 existing innovators that will expand and nuance the findings of the interviews. The resultant consolidation of findings will identify the factors supporting innovation among existing Canadian innovators and would inform the design of learning environments that support innovation education for all students.
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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 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".