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Should PGY‐1 Be Mandatory in Dental Education? Two Viewpoints

2016· article· en· W2548679996 on OpenAlexaff
Vineet Dhar, Alison Glascoe, Shahrokh Esfandiari, Kelly B. Williams, Michelle R. McQuistan, Mark R. Stevens

Bibliographic record

VenueJournal of Dental Education · 2016
Typearticle
Languageen
FieldHealth Professions
TopicDental Education, Practice, Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsLicensureSpecialtyMedical educationViewpointsCurriculumCompetence (human resources)CredentialingCore competencyMedicinePsychologyNursingFamily medicinePedagogy

Abstract

fetched live from OpenAlex

This Point/Counterpoint considers whether a general dentistry postgraduate year one (PGY-1) residency should be required for all new graduates who do not pursue specialty training. Currently, New York and Delaware require PGY-1 for dental licensure, while other states offer it as an alternative to a clinical examination for obtaining licensure. Viewpoint 1 supports the position that PGY-1 should be mandatory by presenting evidence that PGY-1 residencies fulfill new graduates' need for additional clinical training, enhance their professionalism and practice management skills, and improve access to care. The authors also discuss two barriers-the limited number of postdoctoral positions and the high cost-and suggest ways to overcome them. In contrast, Viewpoint 2 opposes mandatory PGY-1 training. While these authors consider the same core concepts as Viewpoint 1 (education and access to care), they present alternative methods for addressing perceived educational shortcomings in predoctoral curricula. They also examine the competing needs of underserved populations and residents and the resulting impact on access to care, and they discuss the potential conflict of interest associated with asking PGY-1 program directors to assess their residents' competence for licensure.

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)0.017
metaresearch head score (Gemma)0.049
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 score0.022
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.049
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.009
Scholarly communication0.0040.006
Open science0.0020.004
Research integrity0.0220.020
Insufficient payload (model declined to judge)0.0030.001

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 head0.090
GPT teacher head0.547
Teacher spread0.457 · 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".

Quick stats

Citations2
Published2016
Admission routes1
Has abstractyes

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