Beyond The Cooperation-Conflict Conundrum: Proceedings of an Arctic Security Webinar Series
Bibliographic record
Abstract
The origins of the conference, for which this volume is the published record, go back to the fall of 2019 and the Canadian Pugwash Group’s (CPG’s) annual general meeting. Having just held a major policy conference at the University of Ottawa on “Speeding Towards the Abyss: Contemporary Arms Racing and Global Security,” the CPG was considering what should be the subject of its next policy conference. Arctic security, in all its dimensions, quickly was identified as the theme to pursue. Planning got underway with a view to holding the event in the fall of 2020 and finding suitable partners.\nThe latter were soon identified in the person of Canada’s foremost Arctic expert, Professor Whitney Lackenbauer, and Trent University as the institutional base. Then COVID-19 intervened to put the kibosh to our tentative timing and our original vision of an in-person gathering.\nWith considerable resourcefulness, the CPG lead, Peggy Mason, and her team, in close collaboration with Whitney Lackenbauer, pivoted to a virtual format, and partnered with the North American and Arctic Defence and Security Network (NAADSN), which Whitney Lackenbauer leads. The Rideau Institute also joined as the third co-sponsor. The organizers recruited a stellar line-up of Canadian Arctic expertise to participate in the conference. In its final form, the conference consisted of six panels featuring two speakers each, covering the full spectrum of Arctic-related issues from climate change to maritime security, and much in between.
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 | 0.019 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.005 |
| Scholarly communication | 0.020 | 0.011 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.035 | 0.011 |
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".