Having opportunities: Children's experiences in a youth recreation centre in a neighbourhood of low socioeconomic status
Bibliographic record
Abstract
Low socioeconomic status (SES) can negatively influence children's development (Bradley & Corwyn, 2002). While research has demonstrated that participation in out-of-school programming can contribute positively in this area, few studies have explored the perspectives of the children who take part in these programs. Place attachment, the conceptual framework employed in this study, is useful for exploring children's experiences with regard to their attachment or bonding to a place and the role that social relationships play in that attachment process (Low & Altman, 1992). The purpose of this qualitative case study was to perform an in-depth exploration of the experiences of children of low SES who participated in a community recreation program (UrbanKidz Youth Centre). Seven children took part in drawing activities and semi-structured interviews. Additional data were collected using observations, field and reflective notes, a focus group interview with adult staff and document analysis. The overarching theme of Having Opportunities emerged from the thematic analysis of the data. The children talked about having opportunities at the centre in three main ways: (a) opportunities to do , (b) opportunities to connect , and (c) opportunities to be . These themes, and by extension, the children's experiences, are discussed within the framework of place attachment (Scannell & Gifford, 2010), and the literature on place, SES and out-of-school programming. Implications for recreation programming and research with children of low SES are also presented.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".