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Record W2135750784 · doi:10.2304/csee.2011.10.2.140

The Erosion of the Public Good: The Implications of Neo-Liberalism for Education for Democracy

2011· article· en· W2135750784 on OpenAlexaff
Catherine Broom

Bibliographic record

VenueCitizenship Social and Economics Education · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIdeologyPublic goodDemocracySociologyLiberalismArgument (complex analysis)Classical liberalismNegotiationMeaning (existential)Democratic idealsForm of the GoodDemocratic educationPublic administrationPolitical scienceEnvironmental ethicsSocial scienceEpistemologyLawPoliticsEconomicsNeoclassical economics

Abstract

fetched live from OpenAlex

This article describes the meaning, history and significance of the concept of the ‘public good’. It begins by theorising the ‘public good’ in relation to literature in the field, particularly Dewey. The public good is understood as an imagined and communal space in which goods valued by society become collectively owned and shared through respectful and open contestation and negotiation. The argument is then made that schools are both part of the public good as well as involved in the development of this concept in students, but that the ability of schools to do this is being damaged by new discourses. Current research and literature in the field of education is used to demonstrate how neo-liberal ideology is eroding this democratic idea. For example, neo-liberal ideology incorrectly positions all goods (including education) as private goods, with damaging consequences for society generally. Its controlling policies negatively affect the ability of schools to educate students about and for the public good, within a democratic conception of society. The article concludes with recommendations that aim to reinvigorate education for the and as a public good in schools. These recommendations are focused on teaching pedagogies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.140
GPT teacher head0.347
Teacher spread0.207 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations10
Published2011
Admission routes1
Has abstractyes

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