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Record W3192810220 · doi:10.1111/padm.12777

Usability of transparency portals: Examination of perceptions of journalists as information seekers

2021· article· en· W3192810220 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePublic Administration · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicE-Government and Public Services
Canadian institutionsnot available
FundersQueen's UniversityIrish Research CouncilQueen's University Belfast
KeywordsTransparency (behavior)CredibilityUsabilityDemocracyPerceptionPoliticsInternet privacyPublic relationsCorporate governanceBusinessOpen dataPolitical scienceComputer scienceLawPsychology

Abstract

fetched live from OpenAlex

Abstract Transparency in public institutions is relevant only in so far as the disclosed information is useful for the stakeholders who access it. Hence, we ask: what do users do with the information they obtain through transparency laws? Despite the growing interest in transparency research, the ways transparency portals are used to gather information remain strikingly understudied. We study the use of proactively and reactively disclosed information under four different transparency laws. Data are collected in the Republic of Ireland through a survey of what is generally considered to be the main category of users, benefiters, and guardians of transparency, namely journalists. This is one of the first surveys of the media's use of resources intended to ensure greater transparency in politics and offers a standard approach to the study of open government as a means to improve democratic governance.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.323
Teacher spread0.295 · 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