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Record W4285595442 · doi:10.1177/13563890221107044

A theory-based approach to designing interventions for Planetary Health

2022· article· en· W4285595442 on OpenAlex
Astrid Brousselle, J. Bradley McDavid, Megan Curren, Rik Logtenberg, Bronwyn Dunbar, Tara Ney

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

VenueEvaluation · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPsychological interventionAction (physics)Management scienceTheory of changeEngineering ethicsField (mathematics)Human healthPublic relationsPsychologyComputer scienceSociologyPolitical scienceMedicineEngineering

Abstract

fetched live from OpenAlex

The current existential crises crystallize an urgent need for us all to contribute to meeting international environmental and social commitments. The message is clear: we need to take action. However, one of the challenges for decision-makers leading the transition is the dearth of practical tools and approaches available. Even in our field, evaluations are still based on practices which systematically overlook important determinants of human health, neglecting what matters most for our societies to thrive. This article aims to build on existing knowledge of program theories, theories of change, and theory-based evaluations to create a practical approach to designing interventions, while taking into account human and natural systems: what is referred to as evaluating for Planetary Health. A key purpose is to explore how we can conceptualize and elaborate interventions, taking into account their implications for Planetary Health, to suggest improvements or alternatives to existing programs, projects, or policies.

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)0.004
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.839
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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)0.0030.000

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 head0.286
GPT teacher head0.428
Teacher spread0.143 · 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