“The Best Home for This Paper”: A Qualitative Study of How Authors Select Where to Submit Manuscripts
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
Introduction: For authors, selecting a target journal to submit a manuscript is a critical decision with career implications. In the discipline of medical education, research conducted in 2016 found that authors were influenced by multiple factors such as a journal's prestige and its mission. However, since this research was conducted the publishing landscape has shifted to include a broader variety of journals, an increased threat of predatory journals, and new publishing models. This study updates and expands upon how medical education authors decide which journal to submit to with the aim of describing the motivational factors and journal characteristics that guide authors' decision making. Methods: The authors conducted five qualitative focus groups in which twenty-two medical education authors and editors participated. During the focus groups participants were engaged in a discussion about how they select a journal to submit their manuscripts. Audio from all focus groups was transcribed. Transcripts were analyzed using codebook thematic analysis. Results: Participants considered multiple factors when selecting a target journal. Factors included a journal's impact, the scope of a journal, journal quality, and technical factors (e.g., word limits). Participants also described how social factors influenced their process and that open access plays a role that could both encourage or deter submission. Discussion: The findings describe the motivational factors and influential signals that guide authors in their journal selection decision making. These findings confirm, extend, and update journal selection factors reported in medical education and other disciplines. Notably, these findings emphasize the role of social factors, relationships and personal experiences, which were absent from previous work. Additionally, we observed increased consideration of open acces and a shift away from an emphasis on journal prestige.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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