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Record W3094390956 · doi:10.5430/irhe.v5n3p8

Academic Identities and Institutional Aims: Critical Discourse Analysis of Neoliberal Keywords on U15 University Websites

2020· article· en· W3094390956 on OpenAlexafffundabout
Sandra G. Kouritzin, Satoru Nakagawa, Erika Kolomic, Taylor Ellis

Bibliographic record

VenueInternational Research in Higher Education · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsUniversity of Manitoba
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIdeologyScholarshipSociologyConstruct (python library)DisciplineCritical discourse analysisPrestigeMeaning (existential)Relevance (law)Logos Bible SoftwareCompetition (biology)Public relationsDiscourse analysisMedia studiesPolitical scienceSocial sciencePsychologyPoliticsLaw

Abstract

fetched live from OpenAlex

Through their websites, universities establish global identities, enabling them to persuade potential students, partners, and research funders of their international prestige, relevance, and unique positioning to prepare students for competition in the global marketplace. They do so through forms of branding such as logos, slogans, images and texts intended to attract potential students, funders and partners. Addressing how website texts construct academic identities and reveal institutional aims, through critical discourse analysis, this paper examines textual discourses found on Canadian U15 Group of Universities’ websites. We focus specifically on how seemingly common-sense keywords are actually rich in ideological and socio-historical meaning. After identifying keywords and concepts across U15 websites, we determined that five themes dominated: University as a corporate entity, University as machine or vehicle, aspirational academic identities, market metaphors, and the doctrine of discovery. Noting the similarities in promotional discourses found across research-intensive university websites, we suggest that university websites communicate and foster neoliberal discourses, ideologies, values, and identities, thereby aligning universities with the values associated with consumer and petro-capitalism rather than with the traditional university ideals of intellectual pursuit, knowledge creation, disciplinary wisdom, good teaching and rigorous scholarship.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.898
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.182
GPT teacher head0.451
Teacher spread0.268 · 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

Citations3
Published2020
Admission routes3
Has abstractyes

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