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Record W2100360862 · doi:10.1177/1362480614531613

The moral economy of security

2014· article· en· W2100360862 on OpenAlexaff
Ian Loader, Benjamin J. Goold, Angélica Thumala

Bibliographic record

VenueTheoretical Criminology · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Security and Public Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSpellMoral economyMoralityOrder (exchange)AmbivalenceSociologyPoliticsConsumption (sociology)Political economyLaw and economicsEconomicsPolitical scienceLawSocial scienceSocial psychology

Abstract

fetched live from OpenAlex

In this article we draw upon our recent research into security consumption to answer two questions: first, under what conditions do people experience the buying and selling of security goods and services as morally troubling? Second, what are the theoretical implications of understanding private security as, in certain respects, tainted trade? We begin by drawing on two bodies of work on morality and markets (one found in political theory, the other in cultural sociology) in order to develop what we call a moral economy of security. We then use this theoretical resource to conduct an anatomy of the modes of ambivalence and unease that the trade in security generates. Three categories organize the analysis: blocked exchange; corrosive exchange; and intangible exchange. In conclusion, we briefly spell out the wider significance of our claim that the buying and selling of security is a morally charged and contested practice of governance.

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)0.006
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.055
Scholarly communication0.0080.008
Open science0.0010.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.040
GPT teacher head0.321
Teacher spread0.280 · 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 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

Citations38
Published2014
Admission routes1
Has abstractyes

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