Getting to Know O’Connor: Experiencing the Ecosystemic Play Therapy Model With Urban First Nations People
Bibliographic record
Abstract
Children’s play behaviors are generally fun for them, but the same cannot be said for children who need clinical help. Play therapy seeks to resolve psychosocial difficulties and reestablish a child’s ability to play and function normally (O’Connor, 2000). Ecosystemic play therapy (EPT) integrates a variety of techniques and theories to create a single model that ‘‘addresses the total child within the context of the child’s ecosystem’’ (O’Connor, 2000, p. 87). Particularly when balancing between a culture of origin, a dominant culture, and the needs of an acculturating child, it is important to use play therapy models that include the caregivers in the therapeutic process (O’Connor, 2005b). The ecosystemic model is that caliber of therapy. This article will act as a catalyst for becoming reacquainted with the ecosystemic model, including a brief history, the major components and techniques, and a case example involving an Urban First Nations family.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.016 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| 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".