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Record W4388140574 · doi:10.1080/01426397.2023.2244430

The past, present, and future of nature and place-based interventions for human health

2023· article· en· W4388140574 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

VenueLandscape Research · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsWestern University
Fundersnot available
KeywordsCuriosityPsychological interventionContext (archaeology)Public relationsScope (computer science)SociologyGlobal healthHealth careEngineering ethicsEnvironmental ethicsPolitical sciencePsychologyMedicineEngineeringSocial psychologyGeographyNursing

Abstract

fetched live from OpenAlex

The benefits of exposure to nature for human health and wellbeing have been evidenced throughout history and across global civilisations. However, research on nature and place-based interventions for human health often centres around a reactive healthcare model rather than fully considering the cultural and historical scope of holistic approaches to health. Adopting a context-setting approach, the article signposts readers to periods, places, and practices which have exemplified or advanced our collective global understanding of health and place. This narrative review demonstrates how different disciplines, and cultural knowledges can provide a foundation to develop nature-based interventions and further curiosity to learn from other practices. The COVID-19 pandemic has changed how some people connect with their environments and consider global health. There is now an opportunity to reflection on, and ethically engage with, different practices and approaches to transition towards a more sustainable future which integrates landscape planning with health promotion.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.000
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 head0.075
GPT teacher head0.421
Teacher spread0.346 · 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