Extending the reach of research as a public good: Moving beyond the paradox of “zero-sum language games”
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
Extending the reach of research as a public good has become widely recognized as a policy priority for research funding organizations in many nations. Yet, there is little academic merit given to such work, presenting scholars with the paradox of a “zero-sum language game” in which they succeed in mobilizing knowledge across discourse communities—such as governments, industry, media, community organizations and the public—at the cost of their success within academic discourse communities. To illustrate this paradox, the article places some focus on the “knowledge mobilization” priority for the Social Sciences and Humanities Research Council (SSHRC) of Canada. The article offers an intersection of discourse theory and game theory to consider how members of academic discourse communities can be understood as players in language games, positioned to make “moves” that change the game-rules, that in turn, permit changes to what are recognized as legitimate, academic discursive practices.
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 | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.020 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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