The effects of discourses in regional contexts on the development of curriculum‐based literacy standards for adolescents in schooling: a comparative study of South Australia and Ontario
Bibliographic record
Abstract
ABSTRACT This study analyses how discourses in regional contexts affect the development of curriculum‐based literacy standards for adolescents in schooling. A comparative case‐study research design enabled the influences of discourses at the regional level to be analysed. The case studies include the development of curricula to define a minimum literacy standard for the final years of schooling for adolescents in Ontario, Canada, and South Australia, Australia. Critical discourse analysis of key texts associated with the development of literacy standards in each region reveals how globally shared meanings about standard setting for schooling interact with other discourses operating in local contexts to produce curricula that define literacy standards. The results indicate that, while a global discourse about standards‐based reforms may be foregrounded in curriculum, locally generated discourses can challenge key ideas associated with a simplistic discourse about standards. Discourses about literacy in Ontario and South Australia contest the assertion that literacy at the end point of schooling can be defined as a basic competency and local meanings associated with literacy are emphasised within the curriculum for each location. Language choices, involving particularly lexical cohesion, complex noun groups and nominalisation, are used to ensure that local meanings inform literacy standards for the endpoint of schooling.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".