Bibliographic record
Abstract
In January 2000, a consortium of 64 universities in Canada signed a historic inter-institutional agreement that launched the Canadian National Site Licensing Project (CNSLP), a three-year pilot project aimed at bolstering the research and innovation capacity of the country’s universities. CNSLP tests the feasibility of licensing, on a national scale, electronic versions of scholarly publications; in its initial phases the project is focused on full-text electronic journals and research databases in science, engineering, health and environmental disciplines. This article provides an overview of the CNSLP initiative, summarizes organizational and licensing accomplishments to date, and offers preliminary observations on challenges and opportunities for subsequent phases of the project. [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-HAWORTH. E-mail address: < getinfo@haworthpressinc.com > Website: < https://www.w3.org/1999/xlink" xlink:href=" https://www.HaworthPress.com "> https://www.HaworthPress.com > © 2001 by The Haworth Press, Inc. All rights reserved.]
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.041 | 0.006 |
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".