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Record W4410856086 · doi:10.4324/9781032724638

What Students Want from their PSHE in Secondary School

2025· book· en· W4410856086 on OpenAlexaff
Angela Milliken-Tull

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsVictoria Park
Fundersnot available
KeywordsPsychologyMathematics education

Abstract

fetched live from OpenAlex

This thought-provoking text stems from the voices of young people in secondary schools, and what they want from their PSHE education. The book focuses on personal development, an aspect of PSHE that is often side-lined in favour of a more topic-based approach, to consider how PSHE lessons can help young people build the knowledge, skills, and character necessary to navigate a fast-changing world. Informed by feedback collected from over 10,000 students on their experiences of PSHE and personal development education, chapters provide suggestions for moving towards solutions that will help teachers improve provision in what is often a tricky topic to teach. The book discusses how the fast-paced changes in today’s world make PSHE particularly difficult to teach and offers advice and guidance on what best practice looks like in such an ever-moving field, along with signposts to further reading and supporting lesson plans. With activities in each chapter to build knowledge and develop skills which students will find useful throughout school and into future study and employment, this book is essential reading for any teacher looking for further guidance in the secondary PSHE classroom.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0050.003
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0180.011

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.

Opus teacher head0.020
GPT teacher head0.281
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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