Book Review of 'Asia Literate Schooling in the Asian Century', edited by C. Halse, London, UK, Routledge, 2015. ISBN 978-0-415-72853-8
Bibliographic record
Abstract
[Extract] The seeming “rise of Asia” and the advent of the “Asian century” has resulted in significant shifts to the gaze Western-orientated countries cast to Asia. Countries such as Australia, New Zealand, and Canada are increasingly challenging their colonial origins to ponder the possibilities of realigning themselves along new geo-political, cultural, and geographical orientations. This realignment takes many forms. In Australia it is referred to as “Asia literacy”, a term of debated origins but one that has nevertheless proved itself to be enduring, though inherently problematic, policy speak. Promoted primarily as an education solution to various economic, strategic, and cultural problems, it has failed to gain traction and widespread acceptance despite over 50 years of promotion by government bodies, policies, and interest groups. A major recurring criticism of the promoted solution is its inherent articulation within dominant instrumentalist discourse and colonial constructs (Salter, 2015; Singh, 1996; Takayama, 2016; Williamson-Fien, 1996).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.056 | 0.023 |
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".