Contentious politics, grassroots mobilization and the Icesave dispute
Bibliographic record
Abstract
In 2008 Iceland experienced the deepest and fastest economic crisis ever recorded in peacetime, which included the total collapse of its financial sector, as well as significant erosion of its currency. This paper concerns a localized protest movement that occurred in the wake of the 2008 crash in Iceland: the mobilization of protest to a settlement deal, known as the Icesave settlement. We interviewed just over 30 actors involved in the mobilization, including politicians, activists, and academics. Our data show that both sides of the Icesave dispute drew on a set of three interwoven narratives, or framings of the debate, that respectively drew on ideas around natural justice, citizenship, and nationalism. Several key discursive intersections between these narratives and the political and economic landscape in the post-economic crisis not only rendered the Icesave dispute salient and commensurate with the experiences of Icelanders living through the crash, but also gave greater credibility to the no-Icesave campaign. We conclude by arguing that the Icesave dispute provides a unique lens onto central questions concerning democracy and the possibilities of meaningful citizen engagement and participation in an era of increasing globalization and of neo-liberal forms of economic governance. Our findings contribute to this literature by revealing some of the particularities of the Icelandic context that were important in creating the socio-historical moment that led to the success of the anti-Icesave movement.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.032 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| 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".