Efficacy of an Interinstitutional Mentoring Program Within Pediatric Rheumatology
Bibliographic record
Abstract
OBJECTIVE: The small size of many pediatric rheumatology programs translates into limited mentoring options for early career physicians. To address this problem, the American College of Rheumatology (ACR) and the Childhood Arthritis and Rheumatology Research Alliance (CARRA) developed a subspecialty-wide interinstitutional mentoring program, the ACR/CARRA Mentoring Interest Group (AMIGO). We sought to assess the impact of this program on mentoring within pediatric rheumatology. METHODS: In a longitudinal 3-year study, participant ratings from the AMIGO pilot program were compared with those after the program was opened to general enrollment. Access to mentoring as a function of career stage was assessed by surveys of the US and Canadian pediatric rheumatologists in 2011 and 2014, before and after implementation of AMIGO. RESULTS: Participants in the pilot phase (19 dyads) and the general implementation phase (112 dyads) reported comparable success in establishing mentor contact, suitability of mentor-mentee pairing, and benefit with respect to career development, scholarship, and work-life balance. Community surveys showed that AMIGO participation as mentee was high among fellows (86%) and modest among junior faculty (31%). Implementation correlated with significant gains in breadth of mentorship and in overall satisfaction with mentoring for fellows but not junior faculty. CONCLUSION: AMIGO is a career mentoring program that serves most fellows and many junior faculty in pediatric rheumatology across the US and Canada. Program evaluation data confirm that a subspecialty-wide interinstitutional mentoring program is feasible and can translate into concrete improvement in mentoring, measurable at the level of the whole professional community.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".