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Record W2768770085 · doi:10.1177/0010414017740601

The Social Construction of Transformative Political Events

2017· article· en· W2768770085 on OpenAlexafffund
Karlo Basta

Bibliographic record

VenueComparative Political Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsMemorial University of Newfoundland
FundersMemorial University of Newfoundland
KeywordsPoliticsContentious politicsTransformative learningFrame analysisSalientArgument (complex analysis)Action (physics)SociologyAgency (philosophy)Social movementMeaning (existential)NationalismPolitical economyEpistemologyPolitical scienceSocial scienceLaw

Abstract

fetched live from OpenAlex

Comparative political scientists have sought to remedy their subdiscipline’s structuralist tendencies by paying greater analytical attention to transformative political events. Yet, our conceptual understanding of events remains rudimentary. The article addresses this conceptual gap in two ways. First, it foregrounds symbolic meaning-making as the constitutive attribute of events. Second, it demonstrates that events are not inherently agency-facilitating by developing the concept of prospectively framed events. These are occurrences that actors know will take place, but of whose outcome they are uncertain. Political challengers frame the upcoming event so as to discursively trap incumbents into political action they would rather not undertake. The article demonstrates this process by tracing the conflict between secessionist challengers and political incumbents within the Catalan nationalist movement between 2006 and 2010. The concluding section discusses the causal implications of the argument.

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 imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.003
Science and technology studies0.0090.072
Scholarly communication0.0130.010
Open science0.0020.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.264
GPT teacher head0.527
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations65
Published2017
Admission routes2
Has abstractyes

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