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Record W2511870452 · doi:10.1109/mpot.2016.2569726

Privacy in Public

2016· article· en· W2511870452 on OpenAlexaff
Avner Levin

Bibliographic record

VenueIEEE Potentials · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsDystopiaInternet privacyAction (physics)Reading (process)Value (mathematics)Computer securityInformation privacyComputer sciencePolitical scienceLawArtificial intelligence

Abstract

fetched live from OpenAlex

This dystopian vision, written almost 60 years ago about a future predicted for a time that is now over 30 years in the past, is closer than it has ever been to becoming a reality. Even mind-reading technology is currently being developed and refined, leading us to an even-more dystopian reality in which our physical bodies will become vessels of surveillance. Überveillance, (omnipresent surveillance) will of course mean the end of privacy as we know it and as we have grown to value it. If we wish to have privacy in the future, we must embark on several courses of action in the present before, as a society, we are too late.

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)0.012
metaresearch head score (Gemma)0.030
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: Commentary · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0060.014
Scholarly communication0.0170.023
Open science0.0020.008
Research integrity0.0100.010
Insufficient payload (model declined to judge)0.0390.010

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 head0.056
GPT teacher head0.319
Teacher spread0.263 · 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
GenreCommentary

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

Citations1
Published2016
Admission routes1
Has abstractyes

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