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Record W1983283170 · doi:10.1177/0270467607311483

Wikisurveillance: A Genealogy of Cooperative Watching in the West

2007· article· en· W1983283170 on OpenAlexaff
Mike Arntfield

Bibliographic record

VenueBulletin of Science Technology & Society · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicAcademic Research and Education Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsLaw enforcementVoyeurismEnforcementZeitgeistPolitical sciencePolice brutalityInternet privacyPublic administrationLawSociologyComputer science

Abstract

fetched live from OpenAlex

This article interrogates the relationship between technology and law enforcement and how changing police surveillance techniques have influenced Western expectations of privacy from the mid-19th century to the present. By examining the evolution of telecommunications devices in particular, the author identifies a diffuse and publicly inclusive system of collaborative data mining maintained by private citizens—a culture of wikisurveillance—as being a technologically determined consequence of police reforms made in 1829 Britain. From the now extinct police signal box to modern AMBER alerts, technology allows the police to be divested of their public presence as mechanical surveillance responsibilities are willingly usurped by private enterprise and largely unaccountable civilians who collectively coauthor and codify the occidental discourse on privacy. As public and private spaces alike become increasingly subject to internal, unregulated monitoring that mimics the police methodology, this article explores the origins of our present zeitgeist of mediated voyeurism.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.994
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0060.010
Scholarly communication0.0050.006
Open science0.0010.003
Research integrity0.0010.001
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 head0.015
GPT teacher head0.306
Teacher spread0.292 · 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.

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

Citations4
Published2007
Admission routes1
Has abstractyes

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