Burden and Characteristics of Unsolicited Emails from Medical/Scientific Journals, Conferences, and Webinars to Faculty and Trainees at an Academic Pathology Department
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
BACKGROUND: Professionals and trainees in the medical and scientific fields may receive high e-mail volumes for conferences and journals. In this report, we analyze the amount and characteristics of unsolicited e-mails for journals, conferences, and webinars received by faculty and trainees in a pathology department at an academic medical center. METHODS: With informed consent, we analyzed 7 consecutive days of e-mails from faculty and trainees who voluntarily participated in the study and saved unsolicited e-mails from their institutional e-mail address (including junk e-mail folder) for medical/scientific journals, conferences, and webinars. All e-mails were examined for characteristics such as reply receipts, domain name, and spam likelihood. Journal e-mails were specifically analyzed for claims in the message body (for example, peer review, indexing in databases/resources, rapid publication) and actual inclusion in recognized journal databases/resources. RESULTS: A total of 17 faculty (4 assistant, 4 associate, and 9 full professors) and 9 trainees (5 medical students, 2 pathology residents, and 2 pathology fellows) completed the study. A total of 755 e-mails met study criteria (417 e-mails from 328 unique journals, 244 for conferences, and 94 for webinars). Overall, 44.4% of e-mails were flagged as potential spam by the institutional default settings, and 13.8% requested reply receipts. The highest burden of e-mails in 7 days was by associate and full professors (maximum 158 or approximately 8200 per year), although some trainees and assistant professors had over 30 e-mails in 7 days (approximately 1560 per year). Common characteristics of journal e-mails were mention of "peer review" in the message body and low rates of inclusion in recognized journal databases/resources, with 76.4% not found in any of 9 journal databases/resources. The location for conferences in e-mails included 31 different countries, with the most common being the United States (33.2%), Italy (9.8%), China (4.9%), United Kingdom (4.9%), and Canada (4.5%). CONCLUSIONS: The present study in an academic pathology department shows a high burden of unsolicited e-mails for medical/scientific journals, conferences, and webinars, especially to associate and full professors. We also demonstrate that some pathology trainees and junior faculty are receiving an estimated 1500 unsolicited e-mails per year.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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