Knowledge Utility: From Social Relevance to Knowledge Mobilization
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
In recent years, a more sophisticated vocabulary has emerged in the field of higher education. Categories such as socially relevant research; knowledge mobilization; research impact; innovation; and university priorities have appeared. At first glance, these words may appear neutral, simple and free from conflicts of interest. However, I argue that each of them requires deeper analysis, especially in relation to current scientific and university public policies, as their use has consequences and/or impacts both at the institutional level (higher education institutions) and actor-level (scholars, project managers, etc.). Therefore, by shedding light on the fact that “social relevance” of university is a commonly addressed category in documents regulating university activities, I postulate that such categories indicate a reductionist notion of “relevance” that is used haphazardly as a substitute for the ideas of meaning, mission, and the aims of a university. In order to pinpoint and discuss these new terms and categories that are used as measures of academic knowledge, the paper focuses on public university systems in Argentina and Canada. From a comparative perspective, I aim at grasping a better understanding of the changes in knowledge mobilization.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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