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Record W1960380014 · doi:10.15353/joci.v8i2.3042

Open Government Data and the Right to Information: Opportunities and Obstacles

2012· article· en· W1960380014 on OpenAlexvenueno aff
Katleen Janssen

Bibliographic record

VenueThe Journal of Community Informatics · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicE-Government and Public Services
Canadian institutionsnot available
Fundersnot available
KeywordsFreedom of informationOpen governmentGovernment (linguistics)LimitingLegislationRight to knowAccess to informationOpen dataBusinessInformation accessPublic relationsPolitical scienceInternet privacyComputer scienceLawWorld Wide WebEngineering

Abstract

fetched live from OpenAlex

This article discusses the relationship between the open government data (OGD) movement and the right to information (RTI) movement. While both movements are closely related, there are some differences that may have a considerable impact on the right of the citizen to access government information. The article argues that the calls for OGD may on the one hand risk limiting the access to government information, while on the other hand they may also provide an alternative source of access to information for existing freedom of information legislation, which is being threatened in some countries.

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)0.035
metaresearch head score (Gemma)0.052
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.052
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0130.056
Scholarly communication0.0260.031
Open science0.0020.025
Research integrity0.0130.018
Insufficient payload (model declined to judge)0.0090.001

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 head0.125
GPT teacher head0.338
Teacher spread0.213 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations140
Published2012
Admission routes1
Has abstractyes

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