Bibliographic record
Abstract
With funding from Canadian Heritage, the seven partners in the Multicultural Canada Project have been able to digitize significant works associated with our multicultural immigrant communities and present them through a single integrated portal on the World Wide Web. The current project will result in the digitization of materials associated with the Chinese, South Asian, Vietnamese, Doukhobor, German, Ukrainian, German and Hungarian communities. Some materials such as the Chinese Times newspaper, provide significant coverage of their communities. Newspapers, photos, letters, and books are included in the online collection. In many cases English and French abstracts and even fulltext are available and searching may be done in English, French and the vernacular. The project also includes learning materials, making the material further accessible to their communities, all Canadians, and the world.\nLed by the Simon Fraser University Library, the project includes library and cultural partners in Canada. The importance of such a project was highlighted at a conference presented in spring 2006 in Vancouver, where community members, libraries, archives and scholars came together to discuss different aspects of the record of multicultural community experience.\nIt is to be hoped that further contributions to the Multicultural Canada portal will continue, and plans are afoot to submit a followup proposal to focus on newspapers.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.022 | 0.002 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.234 | 0.035 |
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".