Critical Practice of Grant Application and Administration
Bibliographic record
Abstract
Researchers experience increasing pressures to connect with bodies that finance their projects. In this climate, critical scholars face many obstacles as they seek to navigate the treacherous waters of securing external funds. To debate these challenges, the ACME Editorial Collective organized a panel for the 2009 Annual Meeting of the Association of American Geographers in Las Vegas. This intervention represents a follow-up discussion and collective writing process among some of the panelists and members of the audience who attended the panel. Below, we examine the neoliberalization of the current funding systems, discuss the implications for research practice, and make suggestions for critical engagement and transformation. Our suggestions, however, will not be easy to implement, as we can infer from the experience of the radical scholars of the post-1968 generation whose ascension into the upper echelons of North American and European university systems was also associated with the neoliberalization of the funding systems. This intervention represents a modest contribution in the tradition of critical research practice of creating the possibilities for progressive change.
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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 | 0.354 | 0.465 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.023 | 0.098 |
| Scholarly communication | 0.051 | 0.032 |
| Open science | 0.007 | 0.024 |
| Research integrity | 0.009 | 0.016 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".