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Record W2025616624 · doi:10.1002/art.38603

A177: Program Evaluation of the ACR/CARRA Inter‐Institutional Mentoring Program (AMIGO) in Pediatric Rheumatology

2014· article· en· W2025616624 on OpenAlexaffabout
Eyal Muscal, Lakshmi N. Moorthy, Meredith Riebschleger, A. Eberhard, Anna Huttenlocher, Marisa S. Klein‐Gitelman, Sampath Prahalad, Kelly R. Stevens, Rayfel Schneider, Peter A. Nigrović

Bibliographic record

VenueArthritis & Rheumatology · 2014
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicinePsychology

Abstract

fetched live from OpenAlex

Background/Purpose: In pediatric rheumatology, the small size of many academic programs translates into limited mentoring options for early career physicians. To address this “mentorship gap,” in 2011 the American College of Rheumatology (ACR) and the Childhood Arthritis and Rheumatology Research Alliance (CARRA) joined together to develop AMIGO, the ACR/CARRA Mentoring Interest Group, that now includes greater than half of pediatric rheumatology fellows and junior faculty in the US and Canada. We report ongoing program evaluation encompassing pilot (2011) and full roll‐out (2012, 2013) phases of the AMIGO project. Methods: Mentees and mentors participating in the AMIGO project were surveyed via online questionnaire to determine dynamics of contact and perceived benefit. The entire pediatric rheumatology community was surveyed in 2011 to determine the state of mentoring and career development, with a repeat survey planned for early 2014. We tabulated the active dyads as of January 2014. Results: As recently reported, detailed evaluation of the pilot phase 17 months after initial roll‐out found that 19 of 20 pilot AMIGO dyads were still functioning, with substantial benefit noted by mentees in career guidance, scholarship, and job satisfaction. Benefits reported by mentors included improvement of their mentoring skills and development of their academic portfolios. Both mentees and mentors reported improved connectedness to the wider pediatric rheumatology community. 83 additional dyads were matched prior to 2012 and 2013 ACR meetings. Comparison of these 17‐month pilot results to a December 2013/January 2014 survey of all active AMIGO participants is ongoing. A questionnaire administered to the whole pediatric rheumatology community in 2011 (n = 135 respondents, including an estimated 64–70% response rate among fellows and junior faculty) found that approximately 60% of fellows and junior faculty had a career development mentor. We will assess whether the AMIGO program has had a global impact upon the mentoring culture in pediatric rheumatology by collecting community‐wide survey data in 2014 and then comparing to 2011 data. Conclusion: The 2011 AMIGO pilot program has confirmed the feasibility of a North American inter‐institutional mentoring program in pediatric rheumatology. Participants identified benefits to both mentees and mentors in multiple domains, most prominently in career guidance, a core goal of the program. Ongoing program evaluation will determine how much of this benefit has been sustained after participation was opened to the whole community, and whether the program has had a measureable impact on the overall state of mentoring in pediatric rheumatology.

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 imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.984
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0030.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.060
GPT teacher head0.417
Teacher spread0.357 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainEvaluation
GenreEmpirical

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".

Quick stats

Citations1
Published2014
Admission routes2
Has abstractyes

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