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Record W3157822671 · doi:10.1386/jdmp_00048_1

Digital dilemmas in the (post-)pandemic state: Surveillance and information rights in South Korea

2021· article· en· W3157822671 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Digital Media & Policy · 2021
Typearticle
Languageen
FieldComputer Science
TopicCOVID-19 Digital Contact Tracing
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDilemmaGovernment (linguistics)Digital rightsState (computer science)PandemicNegotiationNationalismPolitical sciencePublic relationsDigital transformationEconomic growthInternet privacyPublic administrationCoronavirus disease 2019 (COVID-19)LawPoliticsComputer scienceEconomics

Abstract

fetched live from OpenAlex

Drawing on South Korea’s response to COVID-19, this article examines how the digital measures that were implemented by the nation state during the pandemic intensified the dilemma between public safety and information rights. South Korea’s highly praised handling of COVID-19 raises the question of how far digital technology can infiltrate everyday life for the sake of public safety and how citizens can negotiate the rapid digital transformation of a nation state. The South Korean government’s digital measures during the pandemic involved the extensive use of personal data; however, citizens were not allowed sufficient participation in the flow of information. By critically examining the South Korean case, this article reveals that the government coped with the pandemic through digital surveillance as a way to avoid physical lockdown, and in so doing, projected its desire for transition to a digitally advanced state while facilitating nationalism through a digital utopian discourse.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.389
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.012
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 head0.013
GPT teacher head0.252
Teacher spread0.239 · 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