The Peer-Review Process for Articles in Iran's Scientific Journals
Bibliographic record
Abstract
The purpose of this research was to study the peer-review process for articles in Iran's accredited scientific journals. The study considered the types of refereeing currently practised, the decision-making methods and criteria for acceptance of articles, the major decision makers, and the current norms in the peer-review process. The method used was a survey, and the data-collecting tool was a questionnaire. The statistical population of this research included 245 scientific journals. The results of the study show that, currently, the predominant type of refereeing for articles submitted to these journals is ‘double blind’ and the prevailing method of informing authors about the results of manuscript evaluation is ‘commenting on the manuscript after refereeing it and after consideration in an editorial board meeting.’ The findings also indicate that two criteria—‘Originality and creativity of the research’ and ‘Being within the journal's scope’—play the most important role in article acceptance. Of the five main parties cooperating in the peer-review process for these journals, the editorial board plays the most fundamental role.
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
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 | 0.059 | 0.234 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".