Bibliographic record
Abstract
In recent decades, academic science has increasingly been directed toward commercializable ends by neoliberal governments. In this article, I outline a concern that academic scientists have not been consulted about the transformation of science, but nevertheless, in some ways accept commercialization as the way things are done. I focus on the ways in which academic scientists attempt to exercise agency, albeit within the parameters of the neoliberal knowledge economy. In this economy, scientific inquiry has transformed to be focused more on producing marketable products. In order to explore the parameters of scientists’ agency in the context of that transformation, I first elaborate on the idea of agency’s “parameters” and argue that the literature on commercialization lacks attention to how researchers’ agency is encouraged and discouraged in the context of academic research in the United States and Canada; second, I make a case for using the concept of hegemony to understand the ideas and practices of contemporary science; third, I propose a methodological direction that can attend to researchers’ agency in the contemporary context of the neoliberal knowledge economy.
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.
How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Science and technology studies Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
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 | 0.011 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.031 | 0.027 |
| Insufficient payload (model declined to judge) | 0.103 | 0.039 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".