Cutting Close to the Bone: Student Trauma, Free Speech, and Institutional Responsibility in Medical Education
Bibliographic record
Abstract
Learning the societal roles and responsibilities of the physician may involve difficult, contentious conversations about topics such as race, gender, sexual orientation, and class, as well as violence, inequities, sexual assault, and child abuse. If not done well, these discussions may be deeply traumatizing to learners for whom these subjects "cut close to the bone." Equally traumatizing is exposure to injustice and mistreatment, as well as to the sights, sounds, and smells of suffering and pain in the clinical years. This potential for iatrogenic educational trauma remains unaddressed, and medical educators must take responsibility for attending to it. Possible solutions include trigger warnings or statements given to students before an educational activity that may cause personal discomfort. The authors of this Perspective assert, however, both that this concept does not distinguish between psychological trauma and discomfort and that well-intentioned trigger warnings target the wrong goal-the avoidance of distress. Exposure to discomfort not only is unavoidable in the practice of medicine but may be crucial to personal and professional moral development. The authors argue that a more appropriate solution is to create safe spaces for dialogues about difficult topics and jarring experiences. This approach places even the notion of free speech under a critical lens-it is not an end in itself but a means to create a professional ethic dedicated to treating all individuals with excellence and justice. Ultimately, this approach aspires to create an inclusive curriculum sensitive to the realities of teaching and learning in increasingly diverse societies.
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 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 | 0.036 | 0.269 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".