Explaining stability and change of territorial identities
Bibliographic record
Abstract
Abstract A significant body of work examines the presence and strength of territorial political identities (either subnational, national or supranational). A common assumption of this literature is that the presence and strength of these political identities are invariant over time. Given the importance of political identity, it is surprising that this assumption has not been empirically tested. We address this omission by testing this assumption through considering the question of who is most likely to exhibit variation in the reporting of territorial identities and why . We posit that one source of instability in territorially based political identity is rooted in cognitive dissonance which emerges through the interaction of partisanship and electoral outcomes. We explore these questions using panel data from the B ritish Election Study (1997–2001), the C anadian Election Study (2004–2008). Results reveal that the territorial identities of Labour and Liberal partisans, in B ritain and C anada respectively, are compatible with expectations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".