MétaCan
Menu
Back to cohort
Record W4361283618 · doi:10.1080/15700763.2023.2189935

Schoolyard Quality and Opportunities for Well-Being at School: A Citizen-Science Approach to System-Wide Measurement for Equity

2023· article· en· W4361283618 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLeadership and Policy in Schools · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversity of TorontoWilfrid Laurier University
Fundersnot available
KeywordsEquity (law)AccountabilityGeneral partnershipCitizen scienceQuality (philosophy)Work (physics)RecreationPolitical sciencePublic administrationPublic relationsEngineering

Abstract

fetched live from OpenAlex

Schoolyards represent an important opportunity for physical activity, development and learning. However, there is minimal policy or accountability for their level or distribution. Through community partnership and citizen science, we built a system-wide picture of schoolyard quality across Ontario, using a validated, standardized tool. Quality was low with considerable variation. The top-scoring school scored 61 of a possible 88 points, the minimum was 14 (M = 35.3; SD = 9.9). Affluent schools and communities had slightly better playgrounds than poorer ones. Knowledge mobilization about how schoolyards impact health and shortcomings in existing resources raise possibilities for advocacy and policy work.

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)0.010
metaresearch head score (Gemma)0.003
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 score0.241
Threshold uncertainty score0.922

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.472
GPT teacher head0.441
Teacher spread0.032 · 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