MétaCan
Menu
Back to cohort
Record W4377203691 · doi:10.1353/cye.2012.0003

The Green Grass Grew All Around: Rethinking Urban Natural Spaces with Children in Mind

2012· article· en· W4377203691 on OpenAlexaboutno aff
Catherine McAllister, John Lewis, Stephen T. Murphy

Bibliographic record

VenueChildren Youth and Environments · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsnot available
Fundersnot available
KeywordsNatural (archaeology)FeelingPreferencePsychologyOrder (exchange)Natural experimentCognitionGeographySociologySocial psychologyMedicineArchaeologyBusiness

Abstract

fetched live from OpenAlex

In North America's rapidly urbanizing environment, nearby, accessible natural spaces allow children to interact daily with nature, resulting in physical, cognitive, psychological and social health benefits. In order to understand children's current interactions with greenspaces, grade 5 and 6 students in the City of Waterloo, Ontario were interviewed, asked to draw their neighborhoods and indicate their preference on a series of local photographs with varying amounts of natural features. Results were combined with teacher and city official interviews, as well as analyses of strategy and policy documents. According to this study, local children have mixed feelings toward, and minimal contact with, natural areas. Possible causes include fear, liability, decreased outdoor education, and governments that do not consider children to be stakeholders of greenspaces. Barriers to children's relationships with nature could be deconstructed and replaced with bridges such as creative greenspace planning, child involvement and green schoolgrounds.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.012
GPT teacher head0.210
Teacher spread0.198 · 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 designObservational
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

Citations8
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueChildren Youth and EnvironmentsSame topicUrban Green Space and HealthFrench-language works237,207