Discursive space(s) in science curriculum materials in Canada, Australia and Aotearoa/New Zealand
Bibliographic record
Abstract
I examine how science curricula are complicit in maintaining the dominance of knowledge production by major powers, particularly the USA, through their efforts to tell the 'truth' about certain topics, and whether resistant counter-discourses are being mounted, especially in 'peripheral' states such as Canada, Australia, and Aotearoa/New Zealand. I focus on one set of discourses within school textbooks, namely those about space science. My reading of selected textbooks indicates that students are presented with a limited and sanitized version of space science, with a heavy emphasis on US space-science achievements. Overall, attempts to counter this dominance occur through the inclusion of information about 'local' space-science achievements. Nevertheless, there is very little attempt to criticize, problematize or contextualize space science historically, socially and economically, with the result that the textbooks reproduce the discourses of space science promoted by organizations such as NASA.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.007 |
| 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".