Academic Identities and Institutional Aims: Critical Discourse Analysis of Neoliberal Keywords on U15 University Websites
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.016 | 0.029 |
| Scholarly communication | 0.019 | 0.010 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".