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Record W104590376 · doi:10.1177/030437540302800302

Security Assemblages: Airport Security, Flexible Work, and Liberal Governance

2003· article· en· W104590376 on OpenAlexaffabout
Randy K. Lippert, Daniel O’Connor

Bibliographic record

VenueAlternatives Global Local Political · 2003
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsCorporate governanceWork (physics)Airport securityPublic administrationPolitical scienceComputer securityBusinessComputer scienceEngineeringFinance

Abstract

fetched live from OpenAlex

Security has become a more intense focus of public debate and concern following the events of September 11, 2001. In North America, especially, much media and political discourse has centered on the private security workforce charged with the provision of airport security services and, specifically, the quality of service it provides. In response, it is widely claimed that a (1) is occurring in the character of security governance and that we are witnessing a radical shift in the way security workforces airports and elsewhere in society are recruited, trained, and managed. Absent from current debate about security governance is recognition of an earlier, more important development and its intersection with current trends in work and governance. Here we refer to the development of private properties, described by Clifford Shearing and Philip Stenning as a in security governance, (2) and the way in which this development intersects the onset of advanced liberalism (3) a nd the current trend toward the flexibilization of work arrangements associated with the new economy. (4) What has happened since September 11 is less a sea change in airport-security governance and more a problematization of the character of security governance. (5) Efforts to deal with this problematization have far-reaching implications, not only for the way we understand security and its limits but also for the deployment of security assemblages in other domains. In this article, we first discuss previous perspectives on private security, with an eye to both highlighting gaps in this literature and gaining insight into what may be emerging in airport-security governance. In particular, we identify significant omissions concerning the nature of the private security workforce, the ways it is governed, and the as both producer of mass private properties and consumer of security services. This body of research indicates that the processes of commodification combined with the spatialization of mass private properties are important factors to be considered. But in doing so, it can offer only a partial explanation. The provision of security also entails the governance of working populations. We therefore proceed to elaborate a distinct framework, employing concepts such as flexibilization (6) and assemblage (7) drawn from research on the new economy and governmentality, in order to understand the current context of security governance better. From the new-economy literature dealing with the flexibilization of work, we discuss trends in its management and the character of private- and public-sector work; namely, the outsourcing of noncore activities and the creation of quasi-public special agencies. Although the governmentality literature has paid little attention to the governance of work, it is our contention that these forms of governance are consistent with those deemed to operate beyond the state (8) but within advanced liberalism. Consonant with these notions, we demonstrate that a focal point of recent debate about airport-security governance in Canada is the quality of the security workforce conducting passenger screening and how this workforce should be governed. We argue that what has been occurring in airport-security governance since September 11 is neither a return to what came before the quiet revolution nor business as usual. These events have indeed led to a recognition that reducing the cost of delivering public services also tends to reduce both the quality of service and of the workforce that delivers it and that this can have far-reaching effects. Yet, we argue that this recognition is simply that: a recognition of a serious limitation or failure. As such, it is leading not to a sudden, wholesale shift to a new security assemblage but to one that is configured using mostly old parts. In Canada, this new assemblage entails deployment of a new special agency, funded through the responsibilizing strategy of airport user fee s, to govern the airport-security workforce at a distance. …

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)0.004
metaresearch head score (Gemma)0.005
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 score0.016
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0140.072
Scholarly communication0.0160.013
Open science0.0010.014
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0070.001

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 head0.034
GPT teacher head0.395
Teacher spread0.361 · 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

Citations56
Published2003
Admission routes2
Has abstractyes

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