Bibliographic record
Abstract
“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]
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 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.109 | 0.037 |
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".