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Education and training: from public good to private responsibility

2016· book-chapter· en· W4237943925 on OpenAlexaboutno aff
Alan France

Bibliographic record

VenuePolicy Press eBooks · 2016
Typebook-chapter
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsTraining (meteorology)BusinessGeographyMeteorology

Abstract

fetched live from OpenAlex

This chapter explores the way neoliberalism has changed the field of practice in post-16 education and training in the UK, Australia, New Zealand and Canada. While ‘third way’ politics brought a commitment to questions of social justice, neoliberalism was hugely influential in reshaping the way that universities and vocational education and training (VET) providers were to operate. Secondly the chapter will outline the major change brought about around ‘user pays’ philosophy exploring issues of fees and student debt. While this approach has a long history in some countries, by the 21st century it was fully established in the post-16 educational and training sector and, as we shall see, since the crisis it has had substantial impacts on levels of student debt. The final section of this chapter returns us to the question of the widening participation agenda, where we will examine how effective it has been in the UK, Australia, Canada and New Zealand in bringing different social groups into the education and training field

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.041
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.016
Scholarly communication0.0100.007
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0120.002

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 head0.146
GPT teacher head0.390
Teacher spread0.245 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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