Bibliographic record
Abstract
It gives me great pleasure to introduce this Special Issue of Applied Psycholinguistics . One might say that it was very Canadian in its conception. The period between Christmas and New Years 2004 was particularly cold in Montreal and Toronto. It was during this very cold snap that Ellen Bialystok, Fred Genesee, and I decided to apply to the Social Sciences and Humanities Research Council of Canada for special funding to host a conference on bilingualism. To make matters worse, one of our universities only heated its offices to the bare minimum during the holidays, and Ellen Bialystok's furnace broke down. With cold fingers, time running short, and the holiday period in full swing, we nevertheless managed to contact a dozen leading researchers from several countries who consented to become main speakers at the conference, Language Acquisition and Bilingualism: Consequences for a Multilingual Society, held in Toronto in May 2006 (a much warmer event). These researchers were joined by more than 300 people from 34 countries around the world, 119 of whom presented posters of their research (chosen from 250 submissions). The eager response of our research and practitioner communities for the conference and the compelling importance of the policy, educational, and program implications of bilingualism in a global context convinced me, as Editor of the Journal, that we should share the interest of the conference with you, the readers of Applied Psycholinguistics . This Special Issue contains articles by a number of the conference's speakers, and it was jointly edited by Ellen Bialystok and me with the help of Fred Genesee.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".