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Record W2971302170 · doi:10.1097/acm.0000000000002840

In Reply to Boucharel

2019· letter· en· W2971302170 on OpenAlexaffabout
Michael Gottlieb, Sara Krzyzaniak, Teresa M. Chan

Bibliographic record

VenueAcademic Medicine · 2019
Typeletter
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMcMaster University
Fundersnot available
KeywordsScholarshipMentorshipMedical educationAcademic medicineFaculty developmentPromotion (chess)MedicineOfficerEmergency departmentCurriculumSociologyProfessional developmentPolitical scienceNursingPedagogy

Abstract

fetched live from OpenAlex

We thank Dr. Boucharel for her comments on our article. We agree that no single faculty development system functions well without fulsome institutional support. Although programs like the Academic Life in Emergency Medicine Faculty Incubator may increase collaboration, shared learning, and scholarship, it is essential that this endeavor be combined with more systemic efforts aimed at valuing clinician–educators—beyond merely publications.1 As discussed by Chan and Kuehl,2 publication metrics serve as a method of assessing productivity for only some types of scholarship, but undervalue other impor tant scholarly pursuits defined by Boyer (e.g., scholarship of teaching).2,3 This can lead busy academic clinicians to focus their efforts primarily toward publications, while dissuading educators from devoting time to other important endeavors within academics (e.g., curricular design, program administration, didactic lectures, mentorship). To address the challenges facing clinician–educators, institutions must partner with educators to redefine criteria for promotion and tenure, as well as ensure appropriate support for scholarship, teaching, and mentorship. We must reevaluate and properly reward our clinician–educators so we do not lose an essential component of our medical faculty.4 Michael Gottlieb, MDChief academic officer, Academic Life in Emergency Medicine Faculty Incubator, and assistant professor and director of emergency ultrasound, Department of Emergency Medicine, Rush University Medical Center, Chicago, Illinois; ORCID: https://orcid.org/0000-0003-3276-8375.Sara M. Krzyzaniak, MDChief operating officer, Academic Life in Emergency Medicine Faculty Incubator, and clinical assistant professor, Department of Emergency Medicine, and assistant program director, Emergency Medicine Residency, University of Illinois College of Medicine Peoria, Peoria, Illinois; ORCID: https://orcid.org/0000-0002-8173-2750.Teresa M. Chan, MD, FRCPC, MHPEChief strategic officer, Academic Life in Emergency Medicine Faculty Incubator, and associate professor, Division of Emergency Medicine, Department of Medicine, McMaster University, Hamilton, Ontario, Canada; [email protected]; ORCID: https://orcid.org/0000-0001-6104-462X.

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)0.010
metaresearch head score (Gemma)0.112
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.028
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.112
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0060.010
Open science0.0040.004
Research integrity0.0280.057
Insufficient payload (model declined to judge)0.0160.012

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 head0.035
GPT teacher head0.381
Teacher spread0.345 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations0
Published2019
Admission routes2
Has abstractyes

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