Scientific Research in a Democratic Culture: Or What's a Social Science For?
Bibliographic record
Abstract
In attempting to guide both researchers and the federal government in the development of a stronger scientific culture for education research, the National Research Council report, Scientific Research in Education, falls short in its conception of research dissemination. Rather than considering the potential of new publishing technologies to ensure much wider circulation and impact for education research as integral to both its scientific quality and public responsibilities, the report presents a highly circumscribed view of publishing, in terms of disclosing it to professional scrutiny and critique. While this scrutiny and critique are indeed necessary, they are not sufficient if education research is going to play the increased public role demanded of it in the No Children Left Behind Act of 2001. This article builds on the report's reference to education research's parallels with medical research to demonstrate how greater public access to this research has contributed to the democratic quality of people's lives, while arguing that the education research community would do well to explore open access publishing models as one means of extending the desired scientific culture represented by education research.
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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 | 0.122 | 0.112 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.027 | 0.179 |
| Scholarly communication | 0.058 | 0.061 |
| Open science | 0.004 | 0.022 |
| Research integrity | 0.016 | 0.027 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".