Bibliographic record
Abstract
The politics of polarization are intensified in secessionist movements wherein ones culture and identity is questioned; Catalonia is no exception. The drive for independence from Spain has produced divisions between citizens who support or oppose the movement, regardless of their locality. Polarization within the political and academic spheres has only amplified the divergent positions, resulting in echo chambers of stagnant contention and limited opportunities for impactful dialogue. This paper adopts a parallel data collection approach, relying on the elite interviews and political claim analysis to establish the inducement on both sides. We propose an innovative approach to the Catalan crisis through a top-down process via the medias framing and problem definitions. The first section provides an in-depth review and organization of previous literature in order to identify the medias role in framing the issue, the motivations of independence, the position of elites, and the role of the European Union (EU). The second section develops the methodological framework for this project: the elite interviews and political claim coding. The third section cross-analyzes the data sets to rationalize whether the medias framing of the issue has indeed impacted citizens’ perceptions and deepened polarization. Finally, the last section establishes a theoretical framework to examine the academic, social and political implications our findings will have moving forward, specifically focusing on the continued role of the media in framing such prevalent issues. Faculty Mentor: Andrea Wagner Department: Political Science (Honours)
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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.025 |
| Scholarly communication | 0.021 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| 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".