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Record W7009674152

Exploring the Care-Control Nexus Through Police Monitoring of Vulnerable Groups: A Case Study of Project Lifesaver

2023· dissertation· en· W7009674152 on OpenAlexaff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2023
Typedissertation
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNexus (standard)Thematic analysisVariety (cybernetics)AutonomyGovernment (linguistics)Qualitative researchSocial responsibilityWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

Contemporary surveillance practices increasingly pursue the dual objectives of ‘care’ and ‘control.’ For instance, governments increasingly deploy surveillance to protect the health and welfare of those being monitored, though such practices tend to be coercive and prioritize implicit agendas. Thus, it is important to scrutinize emerging forms of ‘protective’ surveillance. This dissertation conducts a qualitative case study of ‘Project Lifesaver,’ a police surveillance program that involves equipping people with cognitive differences who wander (e.g., people who have dementia) with electronic monitoring bracelets so that first responders can track them if they become lost. This work explores how Project Lifesaver is designed, rationalized, and used, and the implications of this surveillance for individuals and society. Using an abductive approach, this study mobilizes Foucauldian theory to illustrate how surveillance logics are (re)shaping social practices. To achieve these aims, this study encompasses content and thematic analyses of a variety of data sources including Project Lifesaver marketing material, observations from international Project Lifesaver events, interviews with caregivers and first responders, and police documents obtained through Freedom of Information requests. Project Lifesaver is rationalized through constructions of ‘risk’ as a necessary protective measure for people who wander and, even more so, as a source of ‘peace of mind’ for their caregivers. Yet, in practice, the program operates primarily as a form of social control, undermining the autonomy and personhood of people with cognitive differences and placing the responsibility of managing their behaviour squarely on their caregivers. Notably, the program seems inherently aligned with police perspectives, treating both wandering behaviour and caregiver program compliance as matters of public security. Moreover, Project Lifesaver appears tailored to suit a distinct policing agenda that is largely unrelated to the protection of vulnerable populations, serving instead as a tool for reducing police operational costs and improving their public legitimacy. These findings prompt reflection on the tensions inherent to how protective state surveillance is framed and how it operates, and the interests prioritized when support for vulnerable groups is entrusted to the police. The state’s expanded use of electronic monitoring, from a punitive security mechanism to a form of population protection, transcends mere repurposing of carceral technology; it signifies the infiltration of carceral logic into the state’s provision of support for those in need. In the context of Project Lifesaver, this manifests in a coercive care practice that objectifies people with cognitive differences and deputizes their caregivers as agents of social control. Simultaneously, it extends the reach of an increasingly militarized and self-serving police apparatus into public health and welfare domains. These outcomes, however, are obscured by the ‘caring’ elements of the surveillance, which position it as in the best interests of all who engage with it. Thus, this study provides an empirical example of how, through protective police surveillance, population care and control not only coexist but collapse into one another.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.075
GPT teacher head0.299
Teacher spread0.224 · 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 teacher head, 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

Citations0
Published2023
Admission routes1
Has abstractyes

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