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The Educational Challenge of Dental Geriatrics

2010· article· en· W2208557077 on OpenAlexaff
Michael I. MacEntee

Bibliographic record

VenueJournal of Dental Education · 2010
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGeriatricsCurriculumMedical educationSociocultural evolutionPerspective (graphical)ConsilienceFoundation (evidence)Health careMedicineHumanismPopulationPsychologyGerontologyEngineering ethicsSociologyPedagogyPsychiatryEpistemologyPolitical science

Abstract

fetched live from OpenAlex

Education in dentistry as in medicine is guided principally by the ontology and theory of science, which provides definitions of health and disease, legitimizes research methods, and influences the role of the clinician. The challenge of managing chronic oral disease and disability prompts interest in social theory as much as science. Therefore, dental geriatrics requires a solid foundation in the humanities from the belief that the determinants of health and the cause of chronic diseases lie within an intermingling of biology, economics, sociocultural structure, and human behavior. The dental curriculum in many places is reorganizing from the horizontal foundation of basic sciences to an integration of foundational and clinical knowledge focused on clinical competencies and integrated care. The impact of this integration on dental geriatrics necessitates a more humanistic and naturalistic perspective in dental education to balance and challenge the current evidence for best clinical practice, which at present is based almost exclusively on science. Consequently, dental students should be exposed to a consilience of the science and the humanities if dentists are to address effectively the needs of an aging population.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.404
Teacher spread0.381 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
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

Citations32
Published2010
Admission routes1
Has abstractyes

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