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Record W2954541945 · doi:10.1177/0967010619850332

The futures of anticipatory reason: Contingency and speculation in the sting operation

2019· article· en· W2954541945 on OpenAlexaff
Sun‐ha Hong, Piotr M. Szpunar

Bibliographic record

VenueSecurity Dialogue · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Security and Public Health
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsSpeculationContingencyFutures contractSecuritizationConceptualizationEpistemologyVisionSociologyFlexibility (engineering)State (computer science)Law and economicsPositive economicsEconomicsPolitical scienceComputer scienceManagement

Abstract

fetched live from OpenAlex

Abstract This article examines invocations of the future in contemporary security discourse and practice. This future constitutes not a temporal zone of events to come, nor a horizon of concrete visions for tomorrow, but an indefinite source of contingency and speculation. Predictive, preemptive and otherwise anticipatory security practices strategically utilize the future to circulate the kinds of truths, beliefs, claims, that might otherwise be difficult to legitimize. The article synthesizes critical security studies with broader humanistic thought on the future, with a focus on the sting operations in recent US counter-terrorism practice. It argues that the future today functions as an ‘epistemic black market’, a zone of tolerated unorthodoxy where boundaries defining proper truth-claims become porous and flexible. Importantly, this epistemic flexibility is often leveraged towards a certain conservatism, where familiar relations of state control are reconfirmed and expanded upon. This conceptualization of the future has important implications for standards of truth and justice, as well as public imaginations of security practices, at a time of increasingly preemptive and anticipatory securitization.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.713
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.313
Teacher spread0.296 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations10
Published2019
Admission routes1
Has abstractyes

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