Expectancies, Values, and Costs of Innovating Identified by Canadian Innovators: A Motivational Basis for Supporting Innovation Talent Development
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Current studies in innovation are often siloed to specific disciplines, precluding a generalizable understanding useful to understanding the factors that promote and hinder individual motivation to innovate. This study integrates analysis of 30 interviews and 500 surveys of Canadian innovators from a variety of disciplines as a means of understanding the avenues that education could use to develop innovation talent. The results of this study point to the overstated role of rewards as drivers of developing innovation talent. These findings support the idea that programs that wish to support innovation for all learners should be guided by the primacy of decisions that build confidence and fulfill interest and perceived importance of the task at hand, as well as those mitigating the costs of innovating. The implementation of promotive and cost-mitigating strategies should be a high priority for educational efforts to stoke the development of innovation talent for learners in many contexts.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it