MétaCan
Menu
Retour à la cohorte
Enregistrement W4206076177 · doi:10.1097/acm.0000000000000918

Stereotype Detox

2015· article· en· W4206076177 sur OpenAlexaffabout
Matthew J. To

Notice bibliographique

RevueAcademic Medicine · 2015
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueInsect and Pesticide Research
Établissements canadiensDalhousie University
Organismes subventionnairesnon disponible
Mots-clésFacilitatorPsychologyNoticePopularityAlcoholics AnonymousSkepticismAddictionDenialPsychoanalysisMedia studiesSocial psychologySociologyPsychiatryLawPolitical science

Résumé

récupéré en direct d'OpenAlex

“Who is here for their first Alcoholics Anonymous meeting?” the facilitator at the front of the room asked. I slowly raised my hand. I was there to observe an AA meeting during my psychiatry block, in the hopes of learning more about the support that was available for people living with alcohol addiction. I was curious to see what the meeting was like; I had no idea what to expect. I tried to suppress the images of addiction that popped into my mind from popular media. “Welcome,” the facilitator said with a smile. As my eyes darted around the room, I couldn’t help but notice that there were people from all walks of life in that church basement, both the young and the old, and that the coffee cups lined the tables. I tried not to look shocked when I saw a young man who must have been around my age. My preconceived notions about the kind of person who attended AA meetings were quickly being dismantled. After a couple of announcements, the facilitator gently led the group in a discussion, and members recounted how they became addicted to alcohol. Some opened up about how they drank uncontrollably, hiding it from family members. Others recalled how friends pointed out to them that something was wrong. One member shared how she drove to another city over an hour away while intoxicated. Someone else reflected on how he had come a long way in recovering from addiction, sharing how he felt hopeless and skeptical at his first AA meeting. I was intrigued to hear their stories, one after another, about how this substance had derailed their lives and how they struggled down the road of recovery. They shared how friends, frontline support workers, and faith helped them through a dark time. Their stories were knit together by a common theme of finding community amongst the group. I could sense the connections between the members who treated each other like family. Those who were further along in their recovery supported those who had recently joined the group, acting as sponsors and mentors to them. I found the honesty surprising. Listening to their conversation challenged my assumptions about people living with alcohol addiction. The unique experiences of each individual showed me that everyone’s story is different. Seeing the diverse group of faces in the room proved that anyone could be struggling with addiction. It reminded me to not rely on stereotypes because my future patients struggling with alcohol addiction will come from many different backgrounds. Treating patients based on stereotypes is unfair and will lead to missed opportunities for them to access essential medical treatment. The meeting also showed me the value of community support, something that is often forgotten in the age of modern medicine. Group members reflected on their failures and successes openly. Although their lives had been negatively affected by alcohol, they recounted how the group listened as they shared their flaws, which significantly helped them with their recovery. My first AA meeting had a much greater impact than I expected. I enjoyed hearing the personal stories, and the experience reminded me to approach each patient in a nonjudgmental and caring manner. I learned the value of referring patients to peer groups and communities, like AA, where they can be encouraged and supported. Community gatherings like these are often overlooked by health care professionals, yet they are the interventions that individuals struggling with addiction are seeking. I left the meeting with a sense of gratefulness for the individuals who shared their stories and a new perspective on caring for my future patients. Matthew J. To M.J. To is a medical student, Faculty of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada; e-mail: [email protected]

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,005
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,109
Score d'incertitude au seuil0,366

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,005
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0020,002
Études des sciences et des technologies0,0060,004
Communication savante0,0040,004
Science ouverte0,0010,004
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,1090,037

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.

Tête enseignante Opus0,205
Tête enseignante GPT0,347
Écart entre enseignants0,142 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueAcademic MedicineMême sujetInsect and Pesticide ResearchTravaux en français237 207