MétaCan
Menu
Back to cohort
Record W2141558969 · doi:10.1177/1524839909357317

The E2D2 Model

2010· article· en· W2141558969 on OpenAlexaff
Lisa Petermann, Graham J. Petz

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.

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)0.010
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.040
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0020.003
Scholarly communication0.0060.007
Open science0.0050.005
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0400.012

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

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 designTheoretical or conceptual
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

Citations2
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueHealth Promotion PracticeSame topicHealth Promotion and Cardiovascular PreventionFrench-language works237,207