The 2004 Canadian National Consulation on Access to Scientific Research Data (NCASRD)
Bibliographic record
Abstract
In mid-June 2004, an expert task Force, appointed by the National Research Council Canada (NRC) and chaired by Dr. David Strong, came together in Ottawa to plan a National Forum as the focus of the National Consultation on Access to Scientific Research Data.nbsp; The Forum brought together more than seventy leaders Canada-wide in research, data management, administration, intellectual property and other pertinent areas.nbsp; This presentation will be a comprehensive review of the issues, the opportunities and the challenges identified during the Forum.nbsp; Complex and rich arrays of scientific databases are changing how research is conducted, speeding the discovery and creation of new concepts.nbsp; Increased access will accelerate even more these changes, creating a whole new world.nbsp; With the combination of databases within and between disciplines and countries, fundamental leaps in knowledge will occur that will transform our understanding of life, the world and the universe.nbsp; The Canadian research community is concerned by the need to take swift action to adapt to the substantial changes required by the scientific enterprise and since no national data preservation organization exists, it is felt that a national strategy on data access or policies needs to be developed. It is also recommended that a Task Force be created to prepare a full national implementation strategy.nbsp; Once such a national strategy is broadly supported, it is proposed that a dedicated national infrastructure, tentatively called Data Canada, be established, to assume overall leadership in the development and execution of a strategic plan.
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 | 0.025 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.010 | 0.000 |
| Scholarly communication | 0.046 | 0.014 |
| Open science | 0.017 | 0.011 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.008 |
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; both teacher heads agree on what is shown here.
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".