Notice bibliographique
Résumé
Dr. Poses appears to misunderstand both the nature of the University of Ottawa Faculty of Medicine's informal conflict resolution policy and how it was used in The Pelican student newsletter matter. His comments oversimplify the debate over the balance that needs to be struck between academic freedom and the importance of maintaining all students' rights to a harassment-free learning environment. Curiously, Dr. Poses ignores his own institution's, Brown University's, comprehensive Policy on Racial/Ethnic Harassment and Discrimination Prevention (revised 7/2001), which recognizes that the “principles and traditions of academic freedom… must be in balance with the rights of others, including the rights of individuals to be free of harassment and intimidation (including sexual harassment).”1 We would like to first correct Dr. Poses' misunderstanding of our informal conflict resolution policy and the Faculty of Medicine's response to the student newsletter. The policy recognizes people's need for an informal forum to work out misunderstandings, disputes, and conflicts before they become full-blown, formal, and public complaints. Often students, faculty, and staff use the conflict officers as a first-step, confidential sounding board to explore how they can, on their own, approach someone about remedying a problem. Other times, the conflict officer assists through confidential mediation. At any time the people involved can decide to drop the issue or pursue their rights through a more formal university complaint process. The policy is not mandatory and recognizes that informal resolution is not appropriate for all disputes. As for The Pelican newsletter, it was the medical students themselves, the peers of the editor and Aesculapian Society, who complained that the publication was harassing and intimidating and who wanted some form of remedial action. This was not, as Dr. Poses suggests, an instance where “officials” took “remedial action” because they “deemed” the student newsletter to be “upsetting or offensive.” In fact, rather than issuing a top-down fiat, the Faculty's conflict officers worked with students from all groups, as well as with the Faculty administration, to respond to all the issues raised. The outcomes described in the article were multifaceted, sensitive to both freedom of speech and a supportive learning environment, and were clearly educational and constructive, not punitive. Most U.S. and Canadian institutions of higher learning have formal policies like those of the University of Ottawa and Brown University that recognize that sexual or other harassment is “not only contrary to the academic mission… to provide students the opportunity to receive full benefit of their education, it is also against the law.”2 While freedom of expression is essential to a university's mission, the statements in The Pelican that women medical students used “feminine wiles” and “toned anorexic bods” rather than medical knowledge to “win points” and “dates” with upper-year classmates and staff hardly rise to the level of free enquiry. Nor did the newletter's mysogynist and racist jokes further the university's mission. As pointed out by both male and female students, these types of statements demean, belittle, marginalize, and generally undermine the targeted students in their academic pursuits. To understand that jokes can be harmful, Dr. Poses need go no further than Brown University's “Information about Sexual Harassment,” which includes “suggestive jokes of a sexual nature or slurs, sexual pictures or displays,… written notes of a sexual nature”3 as examples of sexual harassment. Finally, we would like to reiterate the central theme of our article. There is a significant body of research documenting different forms of mistreatment, discrimination, and harassment in medical schools and describing the long-term effects on the profession. Addressing these concerns requires both formal and informal channels. The University of Ottawa's informal conflict resolution policy and the Faculty of Medicine's early experiences implementing it are offered for their “lessons learned”—in particular, the need to be highly collaborative in designing the structures for informal conflict resolution processes.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».