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Record W2141558969 · doi:10.1177/1524839909357317

The E2D2 Model

2010· article· en· W2141558969 on OpenAlex

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

VenueHealth Promotion Practice · 2010
Typearticle
Languageen
FieldMedicine
TopicHealth Promotion and Cardiovascular Prevention
Canadian institutionsAlberta Health Services
Fundersnot available
KeywordsHealth promotionPsychological interventionIdentification (biology)Cancer preventionIntervention (counseling)Promotion (chess)Quality (philosophy)Population healthPopulationPsychologyMedicineManagement sciencePublic healthEnvironmental healthCancerNursingPolitical scienceEngineering

Abstract

fetched live from OpenAlex

The E2D2 model is a systematic, evidence-informed approach to designing comprehensive and strategic interventions focused on cancer prevention, with potential applications to the broader chronic disease community. The model was developed using an omnibus approach to account for multilevel influences and determinants of individual and population health, quality of life, and cancer risk. It is focused on the four pillars of health promotion and intervention practice (evidence, evaluation, development, and delivery) and moves through three fundamental phases: identification of risk factors and sensitizing concepts; mediating mechanisms and modifiable contexts; and program development, delivery, and evaluation. Distinguished from other models in the health promotion field, the E2D2 model is designed to be both sequential and feedback oriented, which allows for the emergence of new evidence, procedural revisions, and knowledge exchange to occur during any of its phases.

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)0.012
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.958
Threshold uncertainty score0.602

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.051
GPT teacher head0.422
Teacher spread0.371 · 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