The Stata Technical Bulletin and the Stata Journal: editors' report
Bibliographic record
Abstract
The Stata Technical Bulletin (STB ) started publication in March 1991 and ceased in May 2001, after 61 bimonthly issues. It has been succeeded by the Stata Journal (SJ), of which two quarterly issues have so far appeared, 1(1) for the last quarter of 2001 and 2(1) for the first of 2002. Although published by Stata Corporation, the SJ is controlled by an international board including the Editor and Executive Editor and 18 Associate Editors. We believe that the STB was a great success, but by 2001 there was a need for fairly radical change in its content and format. Its role in making available new Stata programs and documentation, whether written by users or by Stata Corp, has largely been superseded by easy and rapid use of the Internet. The SJ continues to be a vehicle for distributing valuable new programs, but it will carry more, and more substantial, expository articles on statistics, data management and graphics using Stata. The SJ is also now a reviewed journal, which we believe is important both for its contributors and for its readers. Finally, the SJ has been redesigned and is now printed on better paper and in more durable covers. We will talk briefly about the transition from the STB to the SJ. Comments and questions about the SJ will be most welcome.
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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 | 0.038 | 0.351 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.013 | 0.024 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.194 | 0.236 |
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".