Perspectives on Play: Learning for Life
Bibliographic record
Abstract
Part 1: The Value of Play? Psychological, Educational and Playwork Perspectives 1. Three Perspectives on Play Pam Jarvis, Avril Brock and Fraser Brown We Don't Play Like That Here: Social, Cultural and Gender Perspectives on Play Yinka Olusoga Part 2: Children at Play: A Journey through the Years 3. Curriculum and Pedagogy of Play: A Multitude of Perspectives? Avril Brock 4. Born to Play: Babies and Toddlers Playing Avril Brock, Jonathan Doherty, Pam Jarvis, Jackie Matthews and Dawn Stevenson 5. Playing in the Early Years: At Liberty to Play Not only Legal but also Statutory! Avril Brock 6. We Want to Play: Primary Children at Play in the Classroom Sylvia Dodds Part 3: Supporting Children's Play 7. Building Social Hardiness for Life: Rough and Tumble Play in the Early Years of Primary School Pam Jarvis 8. Play for Children with Special Educational Needs Verna Kilburn and Karen Mills 9. Playwork Fraser Brown 10. Opening Play: Research into Play and Drama Therapy Phil Jones Part 4. Concluding Perspectives 11. Play, Learning for Life: The Vital Role of Play in Human Development Pam Jarvis, Stephen Newman and Jane George
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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".