Developing a Professionalism and Harassment Policy for Organized Neurosurgery
Bibliographic record
Abstract
Annual conferences, educational courses, and other meetings draw a diverse community of individuals, yet also create a unique environment without the traditional guard rails. Unlike events held at one's home institution, clear rules and jurisdiction have not been universally established. To promote the open exchange of ideas, as well as an environment conducive to professional growth of all participants, the leading neurosurgical professional organizations joined forces to delineate the expectations for anyone who participates in sponsored events. The One Neurosurgery Summit Taskforce on Professionalism and Harassment developed a foundational policy that establishes common expectations for behavior and a unified roadmap for the prompt response to untoward events. We hope that publishing this policy will inspire other medical organizations to establish their own meeting and conference policies. More importantly, we wish to bring greater attention to everyone's responsibility for ensuring a safe and respectful space for education, scientific debate, and networking during organized events.
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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 | 0.099 | 0.156 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.022 | 0.013 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.038 | 0.021 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".