Language, Distance, Democracy: Development Decision Making and Northern Communications
Bibliographic record
Abstract
The Northern Review 41 (2015): 207–240In a country as large as Canada, connectivity—whether by road, rail, radio, or the Internet—plays an important role in economic growth, political and social development, and civic engagement. The importance of communications infrastructure especially is evident in the northern two-thirds of Canada, where radio, television, and the Internet have been instruments of democratic expression and civic participation. As pressures for resource extraction mount, northern communities must respond to economic, social, and political challenges from a position of geographical and, more significantly, “knowledge” isolation. Northern community residents need effective, community-led channels of communication. Addressing these needs will require both social and technological innovation—which can, fortunately, proceed from an existing base of experience and community expertise. In this article, we analyze two moments in northern public policy discourse in which new communications media played a pivotal role in advancing democratic dialogue in northern Canada: the 1975-7 Mackenzie Valley pipeline inquiry, and the 2012-3 hearings into the Mary River iron ore project in Nunavut. Our goal is to advance understanding of the purposeful use of communications infrastructure to support the development of local understanding, citizen engagement, and opportunities for effective community participation in development decisions. We find that technological capacity is foundational, but effective only under specific social and organizational conditions, which include the existence of appropriate institutions at the local level for citizen mobilization and response, dominance of Indigenous language use by northern citizens, appropriate levels of funding, and receptive public institutions to and through which northern citizens can speak.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".