Québec Paradiplomacy in Germany: 50 years in the making.pdf
Bibliographic record
Abstract
This thesis seeks to contribute to the existing literature by investigating the actual practices of paradiplomacy through the case of Quebec paradiplomacy in Germany. The thesis investigates in an exploratory mode how Quebec has been conducting its paradiplomacy in Germany over the last 50 years. The first part presents some of the main scholarly contributions on paradiplomacy and the case of Quebec in order to provide a theoretical background to better understand the rationale behind Quebec’s international action. A second part presents an overall picture of how Quebec has been conducting its paradiplomacy in Germany over the last 50 years. In a first step, the annual reports of the ministry responsible for Quebec’s international relations are analyzed with the qualitative content analysis method to explore the channels used, the sectors of interests, and the activities undertaken from 1970 to 2017. In a second step, the actual practices of Quebec paradiplomacy today are presented by triangulating the information gathered during original interviews conducted with employees of the General Delegation of Quebec in Munich and its Antenne in Berlin with additional written data sources. As such, this research presents an overall picture of how Quebec has been conducting its paradiplomacy in Germany over the last 50 years as groundwork for further research on the actual practices of paradiplomacy and on paradiplomacy between Quebec and Germany.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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".