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Record W3083690998 · doi:10.15353/joci.v16i0.3492

Actionable Open Data

2020· article· en· W3083690998 on OpenAlexvenueno aff
Lucia Lupi, Alessio Antonini, Anna De Liddo, Enrico Motta

Bibliographic record

VenueThe Journal of Community Informatics · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicE-Government and Public Services
Canadian institutionsnot available
Fundersnot available
KeywordsOpen dataWork (physics)Public relationsBusinessPublishingKnowledge managementPolitical scienceComputer scienceWorld Wide WebEngineering

Abstract

fetched live from OpenAlex

Open Data are recognised as invaluable resources at the city level for improving local services, community engagement and businesses initiatives, but their use still struggle to have the desired impact. This work addresses the underuse of Open Data by exploring the connection between data and actions in everyday urban activities implemented by local governments, public agencies, businesses, non-profit organisations and research institutions operating in the city. The empirical results of this exploratory study outline a structural misalignment between a) roles of local actors in city activities and their data-related activities, b) provision of Open Data and information needs of local actors, c) expected uses of data in local actions and forms of support to the users provided by current city Open Data portals. The envisioned alternative approach to foster the use of Open Data at the city level rely on identifying the appropriate data to be produced for supporting local actions, instead than focusing on publishing data disconnected from real information needs of organisations working for local communities.

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 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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.589
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.003
Open science0.0060.002
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 head0.213
GPT teacher head0.387
Teacher spread0.174 · 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 teacher head, not a consensus.

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

Citations5
Published2020
Admission routes1
Has abstractyes

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