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Record W4319836239 · doi:10.1080/25741292.2022.2162255

Adoption of digital technologies amidst COVID-19 and privacy breach in India and Bangladesh

2023· article· en· W4319836239 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

VenuePolicy Design and Practice · 2023
Typearticle
Languageen
FieldComputer Science
TopicCOVID-19 Digital Contact Tracing
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGovernmentalityMateriality (auditing)Coronavirus disease 2019 (COVID-19)Internet privacyPandemicHuman rightsRight to privacyPolitical scienceHackerBusinessPublic relationsSociologyLawPoliticsComputer security

Abstract

fetched live from OpenAlex

This article problematizes the institutional void caused by the lack of accountable digital regulation in India and Bangladesh regarding the adoption of public health-related digital technologies during the COVID-19 pandemic. Findings from literature review and preliminary interviews illustrate an emerged pattern in these countries that intersect governmentality and materiality with an absence of oversight. The findings further indicate an absence of privacy laws that leave citizens vulnerable to privacy breach. As surveillance becomes a social norm, authorities appear to turn a blind eye toward human rights while public remain unaware and uninformed. The article recommends that consumer-centric governmentality is needed to ensure the privacy and protection of consumers and citizens in India and Bangladesh.

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)0.001
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.730
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0000.000
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 head0.068
GPT teacher head0.350
Teacher spread0.282 · 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