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Record W3135795001 · doi:10.1080/00343404.2021.1882671

‘Making blockchain real’: regulatory discourses of blockchains as a smart, civic service

2021· article· en· W3135795001 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueRegional Studies · 2021
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology Applications and Security
Canadian institutionsUniversity of Victoria
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBlockchainCorporate governanceService (business)Government (linguistics)EmpowermentPublic administrationSociologyPublic relationsBusinessPolitical scienceComputer scienceComputer securityEconomicsManagementLawMarketing

Abstract

fetched live from OpenAlex

Policymakers across Canada are considering the blockchain as a way to enable smart(er) governance. Despite the technology’s infancy, jurisdictions perceive smart tools as one of many ways to govern efficiently. Critical geographers, however, remain circumspect of datafication as a value-making process, and have traced myriad ways data-driven technologies participate in the materialization of smart policy mobilities and governance. This article uses autobiography to highlight discourses positioning blockchain technology as a data-driving and -producing civic service. Empirical findings suggest that Canadian policymakers draw on entrepreneurial discourses of digital leadership, transparent data management and digital empowerment to justify their plans in ‘making blockchain real’. These regulatory discourses promote datafication through blockchains as a way to improve government services.

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)0.000
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.769

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.051
GPT teacher head0.321
Teacher spread0.270 · 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