The Northern Voice: Listening to Indigenous and Northern Perspectives on Management of Data in Canada
Bibliographic record
Abstract
The Canadian Cryospheric Information Network and Polar Data Catalogue (CCIN/PDC) provide: (1) a trusted archive to store data from Canadian cryospheric research and (2) a public access portal to this information. The CCIN/PDC has since expanded its collection to include data from health, ecological, social, and other sciences. Since its inception, CCIN/PDC has engaged Indigenous and northern Canadians to understand and meet their information needs. This paper describes three instances of such engagement and next steps for enhanced interaction and support. First, feedback from northern and Indigenous communities led to the development of PDC Lite. Compared to the full-featured online PDC Search application, PDC Lite accommodates slower Internet speeds and allows one to search by particular northern communities. PDC Lite continues to be improved by input from the people that it serves. Next, to facilitate discussion and strengthen collaborative relationships within the polar data community, CCIN/PDC co-hosted two major meetings in 2015. Emerging from both these events was a need to prioritize what has been termed human interoperability and the need to have Indigenous and northern community involvement at all levels of data management. Future plans for CCIN/PDC include more effective partnerships in which we work with and listen to northern and Indigenous Canadians to better understand their requirements for data management services and expertise. Our ultimate goal is to provide, through collaboration with partners, data, information, and expertise that facilitate northern and Indigenous Canadians’ access to publicly-archived data and enable and support management of their own data and resources.
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.082 | 0.027 |
| Scholarly communication | 0.023 | 0.007 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.010 | 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 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".