Understanding Change in Academic Knowledge Production in a Neoliberal Era
Bibliographic record
Abstract
Abstract In this paper, we present and apply a new framework – the Poles of Production for Producers/Poles of Production for Users (PFP/PFU) model – to empirically study how one particular group of academic scientists has responded to neoliberal changes in science policy and funding in Canada. The data we use are from a qualitative case study of 20 basic health scientists affiliated with a research-intensive university in a large Canadian city. We use the PFP/PFU model to explore the symbolic strategies (the vision of scientific quality) and practical strategies (the acquisition of funding and production of knowledge outputs) scientists adopt to maintain or advance their own position of power in the scientific field. We also compare similarities and differences among scientists trained before and after the rise of neoliberal policy. The PFP/PFU model allows us to see how these individual strategies cumulatively contribute to the construction of dominant and alternate modes of knowledge production. We argue that the alignments and misalignments between quality vision and practice that scientists in this study experienced reflect the symbolic struggles that are occurring among scientists, and between the scientific and political field, over two competing logics and reward systems (PFP/PFU).
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.007 | 0.041 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".