MétaCan
Menu
Back to cohort
Record W3135756471 · doi:10.1177/1474904121996134

Making work private: Autonomy, intensification and accountability

2021· article· en· W3135756471 on OpenAlexaboutno aff
Greg Thompson, Nicole Mockler, Anna Hogan

Bibliographic record

VenueEuropean Educational Research Journal · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsnot available
FundersAustralian Research Council
KeywordsAccountabilityAutonomyPublic administrationWork (physics)Argument (complex analysis)Corporate governanceUnderpinningScope (computer science)Public relationsSociologyPolitical scienceEconomicsManagementLaw

Abstract

fetched live from OpenAlex

This paper explores perceptions of work intensification around the world. Underpinning this analysis is C. Wright Mills’ (1959) argument that many personal troubles are public issues, and the notion that a significant dimension of the privatisation of public education, a concern of public education advocates worldwide, is the ways in which school work has become a private issue. One hundred and thirty interviews were conducted with education stakeholders across Australia, England, New Zealand and Canada exploring the issues of work intensification, school autonomy and accountability policies. The paper argues that the work done in public schools is increasingly becoming a private problem as a result of policy interventions. It suggests that we need to widen the scope of defining publicness in education beyond that of governance and funding to include consideration of how work is organised and experienced.

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)0.024
metaresearch head score (Gemma)0.029
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.029
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0120.052
Scholarly communication0.0130.013
Open science0.0010.015
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.283
GPT teacher head0.492
Teacher spread0.209 · 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

Citations31
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Educational Research JournalSame topicYouth Education and Societal DynamicsFrench-language works237,207