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
In 2020 editor-in-chief (Andrew Malekoff) issued a special call for papers for group work stories on pandemic 2020. Among the 28 stories accepted for the series there were 16 from India, 9 from the United States, 2 from Canada and 1 from Israel. General submissions from the U.S., Canada and Israel were typical for the journal. Atypical are submissions from India. Rather than publish the stories in one special issue of the Journal, he decided to spread them out over several issues through 2022. In the course of organizing the special series (with a December 2021 deadline) he continued communication with a few of the authors from India, with particular interest and concern in the deteriorating situation as 2021 unfolded. Although the present commentary is not about group work per se, it is an update by Ajay Saini, Nancy and Andrew Malekoff on the current state of affairs in India, with some contrast to the situation in the U.S., that offers continuing context for the stories in the series.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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