The design of landscapes at child-care centres: Seven Cs
Bibliographic record
Abstract
Key criteria, called Seven Cs, identified from phase one of a five-year multidisciplinary study, are described. This study asked, what are the precise outdoor physical factors that contribute to early childhood development and quality play at child-care centres, and to what degree do these factors currently exist at the centres under study? The child-care setting provides an instrumental context for understanding children and landscape interactions. The Seven Cs criteria were derived from a comparison of 12 sample outdoor play spaces at child-care centres in Vancouver, Canada, with findings from a review of the literature concerning landscapes designed for children. Landscapes designed for children's use should consider developmental and play needs, and the unique contributions that landscapes can offer on a daily basis. Seven Cs earmark important physical dimensions of designed landscapes for children that can potentially enrich future designs at child-care centres. The goal is to provide a set of criteria that will allow the city of Vancouver Community Service and Social Planning Department to evaluate landscape design proposals for new child-care centres and to inform the existing set of Design Guidelines which the city is revising.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".