Vienna Working Papers in Canadian Studies Vol. 2 (2019) Building Bridges, Breaking Barriers: Canada in the 21st Century/Construire des ponts, Franchir les obstacles: Le Canada au 21ème siècle
Bibliographic record
Abstract
The 13th Annual Conference of the Young Scholars’ Forum of the Association for Canadian Studies in German Speaking Countries, entitled “Building Bridges, Breaking Barriers: Canada in the 21st Century,” took place at the University of Vienna June 24-26, 2016. This interdisciplinary and bilingual event sought to reflect on Canada’s ongoing status as a space of encounters and multiculturalism, but also of separatism and (neo)colonial policies. The organizing team aimed at exploring and discussing Canada’s cross-cultural and transnational dimensions; the realities of its histories, geographies, cultures and politics, and, above all, its people and identities that have shaped and transformed it into its current state as a multicultural dominion a mari usque ad mare (“from sea to sea”). For these purposes, the conference brought together 19 postgraduate speakers from Austria, Germany, Switzerland, Canada, and the Czech Republic, whose unique backgrounds and presentations spoke to the diversity of the conference theme and the multitude of perspectives that make up Canadian Studies within and beyond Canada.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.019 | 0.005 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.063 | 0.005 |
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".