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Record W4362545902 · doi:10.32920/22557499

Creating Playgrounds in Collaboration with Children: A Critical Literature Review

2023· preprint· en· W4362545902 on OpenAlexaff
Amy Schoeppich

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsToronto Metropolitan UniversityEducation and Early Childhood DevelopmentYork University
Fundersnot available
KeywordsCitizen journalismPerceptionMultidisciplinary approachPsychologyParticipatory designPublic relationsMedical educationPolitical scienceSociologyMedicineEngineeringSocial science

Abstract

fetched live from OpenAlex

Children engage in play within their communities and as more children live in cities, these experiences often occur on playgrounds. Children have the right to collaborate with adults and make decisions regarding the planning, construction, evaluation and management of these spaces. This critical literature review examined fourteen original, peer-reviewed studies, published between 2004-2020 that focused on children’s participation during the creation of playgrounds. Following an extensive search process across five multidisciplinary databases, the findings were compiled into themes, which included children’s playground design preferences, children’s perceptions of participation and adults’ perceptions of participation. Gaps and inconsistencies within the literature were explored as well as the benefits of participatory research. Finally, recommendations for future playground design projects were delineated including, ongoing communication and involvement in decision-making, learning about children’s rights, providing realistic experiences and engaging in reflective practice.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.047
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0180.018
Science and technology studies0.0030.005
Scholarly communication0.0080.009
Open science0.0020.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.038
GPT teacher head0.385
Teacher spread0.347 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreReview

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

Citations0
Published2023
Admission routes1
Has abstractyes

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