Literacy and Identity Options: A Case Study of Literacy Curricula in a New Brunswick Transnational Education Program in China
Bibliographic record
Abstract
education program in China 1. Context, Existent Literature, and Research Purpose With internationalization being a large part of Canadian educational institutions' strategic plans, Canada recently elevated the priority level of educational cooperation in its bilateral agreement with China. It has promised to expand educational cooperation with China and increase two-way academic mobility (Canada-China Legislative Association, 2012). Lately, there has been a rapid growth of transnational education (i.e., mobility of an education program, institution, or provider between countries) (Knight, 2016). For instance, Canadian programs that provide Canadian curricula in China rose from 48 programs in 2011 (Author A, 2012) to 86 in 2017 (CICIC, 2017). Despite the emerging literature on the cross-border links between Canadian and
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".