COVID-19 and the research scholarship ecosystem: help!
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
OBJECTIVES: Data sharing practices remain elusive in biomedicine. The COVID-19 pandemic has highlighted the problems associated with the lack of data sharing. The objective of this article is to draw attention to the problem and possible ways to address it. STUDY DESIGN AND SETTING: This article examines some of the current open access and data sharing practices at biomedical journals and funders. In the context of COVID-19 the consequences of these practices is also examined. RESULTS: Despite the best of intentions on the part of funders and journals, COVID-19 biomedical research is not open. Academic institutions need to incentivize and reward data sharing practices as part of researcher assessment. Journals and funders need to implement strong polices to ensure that data sharing becomes a reality. Patients support sharing of their data. CONCLUSION: Biomedical journals, funders and academic institutions should act to require stronger adherence to data sharing policies.
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 | 0.395 | 0.816 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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