Bibliographic record
Abstract
This paper examines the discursive construction of the International Baccalaureate (IB) in a 1.5 million word corpus of Canadian newspapers. Combining corpus analysis with the Discourse Historical branch of Critical Discourse Analysis, the study aims to identify discursive strategies employed in the construction of an IB in-group and a non-IB out-group, and suggests they are similar to those evident in discourses of discrimination that marginalise or exclude the outgroup (Baker, Gabrielatos and McEnery 2013a; KhosraviNik 2010; Reisigl and Wodak 2001). While discourses of discrimination tend to be directed at minority groups, in this case, the minority group is the in-group, exhibiting uniformly positive qualities. As a result, a ‘dichotomous world of insiders and outsiders’ (Reisigl and Wodak 2001:105) is created, privileging one and disadvantaging the other. This paper seeks to problematise the seemingly uncritical acceptance and adoption of IB programs in Canada's publicly funded education system.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.009 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.029 | 0.006 |
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".