Abstracts from the Proceedings of the 2006 Annual Meeting of the Association of Directors of Medical Student Education in Psychiatry (ADMSEP)
Bibliographic record
Abstract
The 32nd Annual Meeting of the Association of Directors of Medical Student Education in Psychiatry (ADMSEP) was held June 22nd to June 24th 2006, in Annapolis, Maryland. Approximately 100 registrants from 80 medical schools were in attendance. Plenary sessions, workshops, and posters covered a wide range of educational topics, including issues of professionalism, the challenge of mentoring residents to become teachers, and analyses of psychiatric OSCE cases at various points in the curriculum. Dr. Geoffrey Norman, Canada Research Chair in Cognitive Dimensions of Clinical Expertise at McMaster University, offered the keynote address titled, “Beyond Problem-Based Learning.” In his talk, he argued that the concepts of problem-based learning (PBL) tend to be learned in unsystematic order, which makes it difficult for students to truly learn and understand new material. He suggested that successful transfer of concepts to new problems requires learning from multiple problems. In his talk, he outlined the new curriculum that is being advanced at McMaster (called the COMPASS Curriculum) based on these derived principles of learning and showed how it promised to be superior to “traditional” PBL. More information about the curriculum can be obtained from http://65.39.131.180/ContentPage.aspx?name=COMPASS%20 Home. The 11 abstracts in these proceedings were chosen for their general appeal to medical student educators and because they represent the educational research undertaken by ADMSEP members and colleagues. Included are two task force reports to illustrate the organization's efforts in meeting LCME requirements and a renewed attention to update resources for meeting clinical objectives. The ADMSEP Objectives Taskforce abstract reflects the interspecialty fertilization that underlies ACE. Also included are abstracts from a student study about doctor–patient boundaries and about webbased applications for facilitating administrative responsibilities to a survey of attitudes about who should teach about sexual dysfunction. To appreciate the breadth of topics covered at the meeting, the reader is referred to the full program on the “Meetings” pages of the ADMSEP Web site, http://www.admsep.org.
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 | 0.014 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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; a candidate call from one teacher head, 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".