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Record W2137152344 · doi:10.5539/jsd.v8n2p113

Development of Designing Criteria in Children’s Urban Play Space in Iran- Review of Literature

2015· article· en· W2137152344 on OpenAlexvenueno aff
Noura Marouf, Adi Irfan Che Ani, Norngainy Mohd Tawil, Suhana Johar, Mazlan Mohd Tahir

Bibliographic record

VenueJournal of Sustainable Development · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsnot available
FundersUniversiti Kebangsaan Malaysia
KeywordsSpace (punctuation)Government (linguistics)Process (computing)Local governmentPsychologyBusinessGeographyPublic relationsEnvironmental planningPolitical scienceComputer sciencePublic administration

Abstract

fetched live from OpenAlex

One of the most significant issues related to urban public design is considering outdoor spaces for children to play. Children need to see their environment as a part of their life and learn to protect it. Furthermore, they develop social, emotional, and physical skills by playing outdoors. In some developing countries such as Iran, limited knowledge exists about the state of outdoor play areas for children in cities. This study highlights the need for planners and other land managers to consider the critical importance of the urban environment for play activities of children and its current status in Iran. Literature, studies, opinions and ideas on the value of play and outdoors for children in cities and the limitations of their outdoor play is explored; the issues and points obtained from the literature are analyzed. And the need for further research with children and rethinking for the allocation and design of children’s open space in Tehran is highlighted. Consequently, the criteria to consider children’s play spaces in city of Tehran are proposed. Accessibility, local government involvement, knowledge sharing, appropriate playground design and accounting on children’s voice and view in design process are some criteria which are recommended to promote children’s open space and outdoor play area in Tehran.

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)0.003
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 score0.091
Threshold uncertainty score0.659

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.020
GPT teacher head0.266
Teacher spread0.246 · 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

Citations9
Published2015
Admission routes1
Has abstractyes

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