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Record W2340920886 · doi:10.14288/1.0102165

Relationship of the child to his neighbourhood environment

2011· article· en· W2340920886 on OpenAlexaboutno aff
Robert Morgan Dill

Bibliographic record

VenuecIRcle (University of British Columbia) · 2011
Typearticle
Languageen
FieldMedicine
TopicHuman Health and Disease
Canadian institutionsnot available
Fundersnot available
KeywordsNeighbourhood (mathematics)GeographyMathematics

Abstract

fetched live from OpenAlex

THE AREA OF CONCERN This thesis looks at two actual neighbourhoods within Vancouver - a high density urban, and a low density suburban environment. Using these neighbourhood environments, an attempt is made to see if children act or are affected in ways which can be traced to the layout and amenities of the physical environment. Data has been gathered concerning the physical structure of the environments, and is examined in relation to how the children use these environments, and in relation to the attitudes that parents, or institutions responsible for child socialization, have towards the effect of these environments on the children and themselves. THE METHODS OF INVESTIGATION This data has been gathered by my own observations, by interviewing children and key resource people who work or reside in the neighourhood, and by handing out questionnaires to parents involved with raising children in the sample areas. CONCLUSIONS The data shows that in different types of neighbourhood communities, children use and interact with the environment in different ways. It shows that the behaviour of children is modified because of the physical environment they grow up within. It shows that children of different ages and sexes have differing needs, and that their use of the environment is constantly changing as they grow and search for ways to satisfy these needs. The analysis of this data begins to show deficiencies and strengths in the planning and layout of the physical environments, and how these potentially affect children. From this analysis certain proposed solutions have been arrived at - solutions which the author feels can make the child’s environment more appropriate to his developmental needs,and more in keeping with the desires of his family and self.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score1.000

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)0.0010.000

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 head0.019
GPT teacher head0.187
Teacher spread0.168 · 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.

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

Citations0
Published2011
Admission routes1
Has abstractyes

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