74. Remediation plans: Effectively matching trainee needs to remediation planss
Bibliographic record
Abstract
This paper is a retrospective study reporting on the development of remediation plans for residents who are having difficulty meeting the established program goals and objectives. Additionally, the paper describes the implementation of a consistent, competency focused approach to remediation using a standardized needs assessment and intervention planning tool has functioned to better manage difficulty. First, the paper provides a profile of the educational needs of 20 recent cases describing their specialty programs, training levels and the competency areas of difficulty. Next the paper outlines an educational inquiry tool used by residency program directors to develop, implement and evaluate the trainee’s remediation programs. The tool includes inquiry questions which the faculty answer in the development of a customized remedial educational plan in the such areas as: trainee background, trainee information, overall rationale for remediation plan, training profile, purpose of remediation, details of remediation plan, anticipated outcome of remediation plan, other factors impacting trainee success. The tool is designed to be reviewed with trainee input to ensure the desired outcomes and process for the remediation plan are transparent for both the trainee and program director. Finally three case studies are described in detail including of the types of problems that lead to remediation, examples of the remediation plans developed and the range of approaches employed to support the success of residents. The paper then summarizes the identified key issues and options in optimizing success for residents in difficulty. Christopher I, Doty CI, Lucchesi M. The Value of a Web-based Testing System to Identify Residents Who Need Early Remediation: What Were We Waiting For? Acad Emerg Med 11(3):324. Beeson MS, Jwayyed S. Development of a Specialty-wide Web-based Medical Knowledge Assessment Tool for Resident Education. Acad. Emerg. Med 2004 (Mar); 11(3):324. Boiselle PM. Remedy for Resident Evaluation and Remediation, Academic Radiology 2005(July); 12(7):894-900.
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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 | 0.009 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".