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Record W3124119949

Competition for private and state school teachers

2008· preprint· en· W3124119949 on OpenAlexaboutno aff
Francis Green, Stephen Machin, Richard Murphy, Yu Zhu

Bibliographic record

VenueLondon School of Economics and Political Science Research Online (London School of Economics and Political Science) · 2008
Typepreprint
Languageen
FieldSocial Sciences
TopicSchool Choice and Performance
Canadian institutionsnot available
FundersNuffield Foundation
KeywordsCompetition (biology)Economic shortageQuarter (Canadian coin)Private sectorPrivate educationQuality (philosophy)State (computer science)Labour economicsEconomicsDemographic economicsBusinessPolitical scienceHigher educationEconomic growthGovernment (linguistics)Geography
DOInot available

Abstract

fetched live from OpenAlex

Executive Summary Private schools have historically played an important role in the reproduction of the ruling classes in Britain. They continue to do so, but there is surprisingly little modern research as to how these schools impinge on the economy. In this paper we analyse the role of independent schools in the teachers’ labour market. Teacher shortages in maintained schools are a recurring problem. A potentially relevant factor that has arisen in recent years is rising competition in the teachers’ labour market from independent schools. There has been a huge increase in the demand for education and in particular a rising willingness of the better-off to pay for academic credentials. The fees that better-off parents are prepared to pay for private educational advantage have more than doubled in real terms over the last twenty years, and the average cost of a full private education for a child in day school now reaches six figures, and approximately a quarter of a million pounds for a boarder. The nominal fees have risen by 6% or more every year since 2000. These incomes have given independent schools the means to deploy ever more teaching staff per pupil. We examine the changing quantity and quality of teaching staff in the independent sector, relative to that in the state sector, over the past two decades of rising demand for education. We find that independent schools are employing a disproportionate share of teachers in Britain, relative to the number of pupils they educate, and that the gap between the independent and state sector has been increasing. Independent school teachers are more likely than state school teachers to possess post-graduate qualifications, and to be specialists in shortage subjects. Recruitment from the state sector is an especially important source of new teaching staff for independent schools which has been growing over the medium term. The flows into the independent sector of both newly qualified and experienced teachers, trained at the state’s expense, constitute a small though increasing deduction from the supply of new teachers available to state schools. Inter-sectoral flows depend on the attractions of jobs and accordingly we also investigate how working conditions and wages vary between the sectors and over time. Independent school teachers work with fewer pupils and enjoy longer holidays and, in the case of women, shorter weekly hours. The level of job satisfaction over hours and the work itself was higher in private schools in the early to mid 1990s, but there is evidence of some convergence in job satisfaction since then. Among women, pay is lower in the private sector, which we interpret as a compensating differential. For men, there is no significant inter-sectoral difference in pay. However, for both men and women there is evidence of a substantial pay premium for independent-school teachers trained in shortage 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 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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0430.002

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 head0.078
GPT teacher head0.399
Teacher spread0.321 · 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 designObservational
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
Published2008
Admission routes1
Has abstractyes

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