Bibliographic record
Abstract
Physical Education 5-11 is about lighting or relighting a fire in all those who have the privilege and the responsibility of teaching children physical education in Primary schools today. It is written at a time of great change: a revised Primary curriculum; an increased drive to raise achievement and potentially a narrowing of curricular scope in favour of literacy and numeracy. It is little wonder that teachers are looking for certainty and answers to questions such as:- What do I teach in PE? What do I need to know about children’s development? What does good teaching look like in PE? How can I assess such a practical subject effectively? This new and updated edition provides answers to those questions, covers issues in Physical Education and provides a wealth of practical advice on teaching across the stages of the new 2014 curriculum. Drawing upon the author’s experiences as a teacher, coach, lecturer and adviser, it delivers a justification for PE as an essential element in the Primary curriculum, imbues a theory into practice approach that provides readers with clarity, instils confidence and offers a licence to teach all practical aspects of PE effectively and creatively underpinned by knowledge of children’s development, their learning and the critical professional issues in PE today. This book is the essential companion to inform and inspire students and practising teachers in this most dynamic and exciting of subjects!
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.366 | 0.191 |
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".