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Record W2895749759

Location Tracking by Police: The Regulation of ‘Tireless and Absolute Surveillance’

2018· article· en· W2895749759 on OpenAlexaboutno aff
Bert‐Jaap Koops, Bryce Clayton Newell, Ivan Škorvánek

Bibliographic record

VenueUC Irvine law review · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsnot available
FundersNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsSeriousnessContext (archaeology)Internet privacyTracking (education)PhoneAnonymityLicenseSecrecyComputer securityPolitical scienceBusinessLawComputer scienceGeographySociology
DOInot available

Abstract

fetched live from OpenAlex

Location information reveals people’s whereabouts, but can also tell much about their habits, preferences, and, ultimately, much of their private lives. Current surveillance technologies used in criminal investigation include many techniques to track someone’s movements; not all are equally intrusive. This raises the following questions: how do jurisdictions draw boundaries between lesser and more serious privacy intrusions? What factors play a role? How are geolocational privacy interests framed? In this Article, we answer these questions through a comparative analysis of location-tracking regulation in eight jurisdictions: Canada, Czechia, Germany, Italy, the Netherlands, Poland, the United Kingdom, and the United States.\nWe analyze the legal status of location tracking through human observation, GPS tracking, cell-phone tracking, IMSI catchers (Stingrays), silent SMS, automated license-plate recognition, and directional Wi-Fi tracking in these countries. This results in highly context-dependent and case-specific assessments, in which eight factors play a role: use of a technical device, place, intensity, duration, degree of suspicion, object of tracking, covertness, and active generation of data. At a deeper level of analysis, we identify different conceptualizations of privacy underlying these assessments: not only classic privacy frames, such as communications secrecy, protection of home and body, and informational privacy, but also two new privacy frames: freedom of movement in combination with anonymity, and the mosaic theory. Thus, we discern a tentative but unmistakable shift in how lawmakers and courts assess the intrusiveness of location tracking, particularly of people’s movements in public space.\nTraditional privacy frames tend to downplay the seriousness of the privacy infringement enabled by location tracking, and our analysis demonstrates an increasing discomfort with this tendency, leading to the emergence of novel privacy frames (or theories) to regulate what might easily turn into what the Supreme Court of the United States has called “tireless and absolute surveillance.” We conclude that legal privacy frameworks developed in past centuries prove ill-suited for assessing the privacy-intrusiveness of contemporary location-tracking investigation methods, and that emerging, novel frameworks for understanding and protecting privacy may provide lawmakers and courts with the tools needed to address the challenge of preserving (geolocational) privacy in the twenty-first century.

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)0.007
metaresearch head score (Gemma)0.021
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: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.164

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0040.018
Scholarly communication0.0060.005
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.356
Teacher spread0.317 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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