Bibliographic record
Abstract
This interdisciplinary project examines discourses of internet in Nunavut, a territory in Northern Canada. It has two main arguments: that internet in Nunavut is implicated in correlated discourses of frustration and potential, and that internet in the territory is articulated as having multiple faces and facets. Internet in Nunavut, this thesis argues, is experienced as a media technology, as a tool for communication, as political, as failing and frustrating, as online content, as physical infrastructure, and as potential. In making its arguments, the thesis engages with debates about internet governance, the cultural specificity of internet, and the definition of internet itself. Primary research methods for this thesis included: interviews conducted over the telephone or Skype in London (UK), face to face interviews in Ottawa, Toronto and Iqaluit, the analysis of archival materials (in particular, government reports), as well as a limited period of participant-observation at the Community Access Program site in Iqaluit (the capital of Nunavut). The first empirical chapter in the thesis (Chapter 4: “So frustrating”) examines narratives of Nunavummiut users concerning their experiences of internet; the second (Chapter 5: Fractious Collaborations) examines how some Northern internet activists have lobbied the federal government to alter its internet policy, as a means of tapping into Nunavummiut internet's potential; and the third (Chapter 6: A Local Connection) and final empirical chapter explores the Community Access Program (which provides internet access free of charge to the Nunavummiut public), as a means of linking macro-perspectives and discourses of internet
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.036 | 0.027 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".