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Record W2147766752 · doi:10.1177/1057567707306643

Surveillance, Security and Social Sorting

2007· article· en· W2147766752 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Criminal Justice Review · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsQueen's University
Fundersnot available
KeywordsCivil libertiesCorporate governanceIdentification (biology)Social securitySortingPolitical sciencePublic relationsSociologyComputer securityPublic administrationBusinessLawPoliticsComputer science

Abstract

fetched live from OpenAlex

Security requirements have been raised to a high level in nation-states around the world following the 9/11 attacks. The resulting increase in routine surveillance of citizens, and especially of travelers, raises questions of sociological interest regarding the intensified means of technology-dependent governance common to many countries. The quality of social existence in a globalizing world is directly affected by the automated identification and social sorting systems proliferating especially at borders but also in everyday life. This article addresses two aspects of post-9/11 security and surveillance: the proliferation of new airport security measures and the emergence of the globalized ID. In both cases, standards are being harmonized such that similar measures are in place at many airports around the world and similar national ID card-and-registry systems are being established, each capable of sharing personal data cross-nationally. Implications for governance in general and civil liberties in particular are explored and critiqued.

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.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.960
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.038
GPT teacher head0.388
Teacher spread0.350 · 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