Prose, Psychopaths and Persistence: Personal Perspectives on Publishing
Bibliographic record
Abstract
The process of attempting to publish a paper in a refereed journal can be rather stressful. This paper presents a number of personal reflections on the publishing process, with the aim of helping aspiring journal authors to appreciate the nature of the challenge, and some of the requisites for success. The challenges in dealing with referees include the element of luck involved in securing sympathetic referees, the poor quality of the reports prepared by some referees, and the slowness of the review and editorial process. A number of examples from my experiences in agricultural economics journals are presented. These reveal that one of the most important characteristics that a journal author needs is persistence. Publier un article dans un périodique scientifique s'avère parfois une tâche éprouvante. L'auteur nous fait part de ses réflexions sur le monde de l'édition, le but étant d'aider les auteurs en herbe à apprécier la nature du défi et de comprendre certaines conditions préalables au succès. Trailer avec un comité de lecture anonyme suppose une certaine intervention du hasard. En effet, il faut non seulement dénicher des lecteurs bienveillants mais aussi composer avec la piètre qualité de certains comptes rendus et la lenteur du processus de lecture et de correction. Suivent maints exemples tirés de périodiques d'économie agricole. Ces exemples révèlent qu'une des principales qualités des auteurs d'articles pour périodique scientifique est la ténacité.
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 | 0.051 | 0.098 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.026 | 0.081 |
| Scholarly communication | 0.037 | 0.032 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.007 | 0.015 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".