Bibliographic record
Abstract
This essay, part of “Data Strategy in the Digital Age—Special Report”, a collection of essays commissioned by the International Law Research Program at the Centre for International Governance Innovation (CIGI), exploring topics including the rationale for a data strategy, the role of a data strategy for Canadian industries, and policy considerations for domestic and international data governance. The essay notes that a major challenge in thinking about a national and international “data strategy” stems from the fundamental tensions between what information “wants” to be: free and shared, but also expensive, owned and controlled. Sometimes, information “wants” to be dangerous. Contemporary discourse around the governance of information often refer to data as “the new oil” or “the new gold”. These metaphors imply ownership and exclusive control and emphasize the money that can be made by those who control data—the private benefits that they might derive from its exploitation, not the aggregate value shared by society as a whole—while ignoring that much more is at stake. The essay suggests using a better metaphor: data as “the new sea.” Unlike oil or gold, but like the sea, data and information are non-rivalrous resources that can be used simultaneously by everyone without being diminished. Built around similar tensions between what the sea “wants to be”: free, shared and open; expensive and owned; empowering and dangerous; the law of the sea and its historical development provide a useful framework for thinking about the national and international governance of data.
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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.022 | 0.034 |
| Scholarly communication | 0.032 | 0.013 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".