A Qualitative Discourse Analysis of Ontario University Websites: Exploring the Value Systems of Teacher Education Webpages
Bibliographic record
Abstract
Although features of hidden curriculum (implicit value systems) in higher education have been extensively researched (Snyder, 1971;White, 1988), few studies have undertaken research that explores hidden curriculum using curriculum theory in conjunction with Systemic Functional Linguistics.The present study explored the hidden curriculum implicit within descriptions of Teacher Education (TE) programs on three Ontario faculties' webpages.The study drew textual data from open source documents and webpages that are publicly accessible on websites (i.e., from the Ontario College of Teachers'; Ottawa; Queen's; and Nipissing Universities).Analysis focused on, 1) the Commonplaces of Curriculum (Connelly & Clandinin,1988); and 2) Systemic Functional Linguistics: Mood, Transitivity, and Theme (Halliday & Matthiessen, 2004; 2014), to identify the recurring patterns of emphasis and de/emphasis in the texts.Findings suggested that features of the market-oriented value system constrain the inclusive, and diverse pedagogy that is prevalent in teacher education programs.Implications are discussed.
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.015 | 0.018 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".