NEW PERSPECTIVES AND ISSUES IN EDUCATIONAL LANGUAGE POLICY: IN HONOUR OF BERNARD DOV SPOLSKY. <i>Robert L. Cooper, Elana Shohamy, and Joel Walters (Eds.)</i>. Amsterdam: Benjamins, 2001. Pp. vi + 307. $98.00 cloth.
Bibliographic record
Abstract
Bernard Dov Spolsky is certainly deserving of a festschrift honoring his work: His career, which has taken him from New Zealand to Australia, to Israel, and to Canada and the United States, and back again to Israel, is one that has made a huge impact on the field of educational linguistics broadly conceived. His work includes major contributions with respect to Maori and Navajo educational programs, bilingual education in North America, and issues related to language policy studies and minority language education around the world. His commitment to issues of social justice and equity is well known and well articulated in his work and in his life, and this commitment is also clearly reflected in the contributions to this volume.
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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.013 | 0.022 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".