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Record W2157890287 · doi:10.29173/irie118

Using a Social-Ethical Framework to Evaluate Location-Based Services in an Internet of Things World

2014· article· en· W2157890287 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe International Review of Information Ethics · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsnot available
Fundersnot available
KeywordsInternet of ThingsThe InternetControl (management)Computer scienceTracking (education)Element (criminal law)Internet privacyCore (optical fiber)World Wide WebComputer securityData scienceBusinessTelecommunicationsSociologyPolitical scienceLawArtificial intelligence

Abstract

fetched live from OpenAlex

The idea for an Internet of Things has matured since its inception as a concept in 1999. People today speak openly of a Web of Things and People, and even more broadly of an Internet of Everything. As our relationships become more and more complex and enmeshed, through the use of advanced technologies, we have pondered on ways to simplify flows of communications, to collect meaningful data, and use them to make timely decisions with respect to optimisation and efficiency. At their core, these flows of communications are pathways to registers of interaction, and tell the intricate story of outputs at various units of analysis- things, vehicles, animals, people, organisations, industries, even governments. In this trend toward evidence-based enquiry, data is the enabling force driving the growth of IoT infrastructure. This paper uses the case of location-based services, which are integral to IoT approaches, to demonstrate that new technologies are complex in their effects on society. Fundamental to IoT is the spatial element, and through this capability, the tracking and monitoring of everything, from the smallest nut and bolt, to the largest shipping liner to the mapping of planet earth, and from the whereabouts of the minor to that of the prime minister. How this information is stored, who has access, and what they will do with it, is arguable depending on the stated answers. In this case study of location-based services we concentrate on control and trust, two overarching themes that have been very much neglected, and use the outcomes of this research to inform the development of a socio-ethical conceptual framework that can be applied to minimise the unintended negative consequences of advanced technologies. We posit it is not enough to claim objectivity through information ethics approaches alone, and present instead a socio-ethical impact framework. Sociality therefore binds together that higher ideal of praxis where the living thing (e.g. human) is the central and most valued actor of a system.

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)0.011
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.903
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.087
GPT teacher head0.433
Teacher spread0.347 · 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