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Record W2244240439 · doi:10.2304/pfie.2013.11.4.364

Neoliberal Universities and the Education of Arts, Humanities and Social Sciences in Bangladesh

2013· article· en· W2244240439 on OpenAlexaff
Sardar M. Anwaruddin

Bibliographic record

VenuePolicy Futures in Education · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Educational Policies and Reforms
Canadian institutionsInstitute for Christian StudiesUniversity of Toronto
Fundersnot available
KeywordsThe artsDemocracyHigher educationNeoliberalism (international relations)PhenomenonSociologySocial sciencePolitical scienceEducation policyLiberal arts educationPublic administrationPoliticsLaw

Abstract

fetched live from OpenAlex

In this article, the author explores the neoliberal impacts on higher education in Bangladesh, how market-driven policies might limit the education of arts, humanities and social sciences, and whether or not this phenomenon may have consequences for the future of democracy in the country. First, the author focuses on the privatisation of higher education in the 1990s and the World Bank's influences on education policies, with specific reference to a recent policy reform initiative. Second, he takes a comparative look at the types of degree programmes offered by both public and private universities in Bangladesh. Finally, he situates his discussion in Martha Nussbaum's arguments to initiate a debate about whether or not the neoliberal universities' negligence in the education of arts, humanities and social sciences has implications for a strong and sustainable democracy.

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)0.005
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 score0.025
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.009
Scholarly communication0.0040.003
Open science0.0000.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.017
GPT teacher head0.332
Teacher spread0.315 · 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

Citations16
Published2013
Admission routes1
Has abstractyes

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