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Record W2968555630 · doi:10.1080/02701960.2019.1647835

Gerontology competencies: Construction, consensus and contribution

2019· article· en· W2968555630 on OpenAlex
JoAnn Damron‐Rodriguez, Janet C. Frank, Robert J. Maiden, Janice Abushakrah, Jan Jukema, Birgit Pianosi, Harvey L. Sterns

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGerontology & Geriatrics Education · 2019
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsHuntington University
FundersCouncil for Higher EducationDivision of Graduate EducationYoungstown State UniversityYükseköğretim KuruluUniversity of Utah
KeywordsAccreditationWorkforceDelphi methodMedical educationAging in the American workforcePsychologyCompetence (human resources)GerontologyMedicinePedagogyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

The Academy for Gerontology in Higher Education (AGHE) in 2014 approved the first integrative "Gerontology Competencies for Undergraduate and Graduate Education"©. This article describes the background, thought development, guiding framework and consensus process for its construction. A modified Delphi method utilizing seven review rounds within three developmental cycles, with gerontology educators from 30 institutions, achieved input and consensus. The comprehensive framework has ten major domains, employs three categories each including multiple selective competencies. Six Category I competencies are essential orientations to gerontology. Four Category II competencies are "interactional" processes of knowing and doing across the field. Category III provides eight selective competencies for sectors where gerontologists may work. From educators' feedback, gerontology characteristics emerged: multi-system approaches; interdisciplinary; communication of older adults' "voices" and strengths; research utilization. The discussion includes the contribution of competency-based gerontology to students and aging workforce development as well as next steps, outcome measurement, levelling and accreditation.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.415
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.028
GPT teacher head0.346
Teacher spread0.318 · 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