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Record W2736021818 · doi:10.21815/jde.017.052

Introduction to “Advancing Dental Education in the 21<sup>st</sup> Century” Project

2017· article· en· W2736021818 on OpenAlexaboutno aff
Howard L. Bailit, Allan J. Formicola

Bibliographic record

VenueJournal of Dental Education · 2017
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipDental educationMedical educationStrategic planningPolitical scienceMedicineLibrary sciencePublic relationsManagement

Abstract

fetched live from OpenAlex

In 1926, the Carnegie Foundation for the Advancement of Teaching published a report prepared by William J. Gies, PhD, a professor of biochemistry and founder of the Columbia University College of Dental Medicine. The Gies report examined the current status of dental education in the United States and Canada and made recommendations for a new direction. This report led to major improvements in dental education and research and was a critical factor in making dentistry a learned profession. Dental and allied dental education are now challenged by a new set of issues related to financing education, improved oral health, more effective treatment technologies, and a rapidly changing delivery system. In an effort to meet these challenges, this strategic planning project first examined the current status and future trends that are likely to impact the dental profession over the next 25 years. The project was organized into six sections, and 50 authors were invited to prepare 38 articles to address these issues. The executive summaries for each section are being published in the August and September 2017 issues of the Journal of Dental Education, and the background articles are being published in online supplements to those issues. In the next phase of the project, information from the articles will be used to make strategic recommendations to assist dental schools and allied dental education programs in preparing graduates for practice in 2040 and to meet their institutions' missions for scholarship and service. This introduction presents the project rationale, provides a list of the published articles, and acknowledges the organizations that supported this effort.

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)0.011
metaresearch head score (Gemma)0.008
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: Editorial · Consensus signal: none
Teacher disagreement score0.053
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0030.003
Scholarly communication0.0080.004
Open science0.0020.008
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0530.031

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 head0.010
GPT teacher head0.362
Teacher spread0.352 · 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
GenreEditorial

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

Citations14
Published2017
Admission routes1
Has abstractyes

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