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Record W6986982856

Representing the Promotional University: Undergraduate Student Recruitment Strategies in Ontario, 1997- 2007

2009· article· en· W6986982856 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Sustainability and Education
Canadian institutionsnot available
Fundersnot available
KeywordsIdeologyRhetorical questionInstitutionWork (physics)Gloss (optics)Balance (ability)
DOInot available

Abstract

fetched live from OpenAlex

This thesis explores the promotional activities of five Ontario universities, bringing together scholarly work in history, education, marketing, consumer culture, semiotics, representation, and ideology to consider how institutions portray themselves to prospective undergraduate students. Visually and textually, each institution now constructs a brand, positions itself competitively, and shapes the ways in which it desires to be perceived. In promotional materials, universities attempt to balance conflicting roles as both cultivators of culture and the liberal arts, as well as centers of innovation and training in the “knowledge economy.” It is concluded that, in promotional materials, universities take the rhetorical middle ground, claiming to have the best of both worlds. They gloss over conflicting agendas, idealize the academic environment, and contribute to a “student consumer” mentality among prospective students by emphasizing convenience, credentials, and career prospects.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.956
Threshold uncertainty score0.383

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0150.002
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.095
GPT teacher head0.320
Teacher spread0.225 · 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 designObservational
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

Citations1
Published2009
Admission routes1
Has abstractyes

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