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Record W3013037179 · doi:10.1093/heapro/daaa023

Interdependence between health and peace: a call for a new paradigm

2020· article· en· W3013037179 on OpenAlexaff
Izzeldin Abuelaish, Michael S. Goodstadt, Rim Mouhaffel

Bibliographic record

VenueHealth Promotion International · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Conflict Studies
Canadian institutionsPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsPublic healthPremiseMental healthHealth policyHealth belief modelPublic relationsPolitical scienceSociologyPsychologySocial psychologyHealth promotionCriminologyMedicinePsychiatryEpistemologyNursing

Abstract

fetched live from OpenAlex

Health and peace, and their relationships to disease/conflict/violence, are complex and multifaceted interrelated terms. Scholars have proposed a variety of definitions for health and peace. The conceptualizations of health and peace share many fundamental elements, including in their social, psychological (emotional and mental) and spiritual dimensions. We argue that health and peace are inter-dependent in a fundamental causal fashion. Health is always positively or negatively affected by conflict; peace can be directly or indirectly fostered through public health program and policy initiatives. Evidence shows that public health professionals and academics have frequently failed to recognize the inter-dependence of health and peace when conceptualizing, and addressing, issues related to health and peace. In contrast, the present article argues in support of a new paradigm for addressing public health issues related to health and peace; such a paradigm is based on the premise that health and peace are inextricably linked, requiring that they be addressed in an integrated, inter-dependent, fashion. Finally, we emphasize that fostering health and peace requires identifying and promoting positive socio-ecological influences on health, rather than limiting our focus to health deficits and obstacles at the individual or community levels.

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)0.001
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.573
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.283
GPT teacher head0.514
Teacher spread0.231 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations19
Published2020
Admission routes1
Has abstractyes

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