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Record W4281382427 · doi:10.1002/cjas.1676

Virtual forums for public accountability: How internet and communication technologies are influencing citizen interactions with a local government

2022· article· en· W4281382427 on OpenAlexaffvenueabout
Sina Bahramirad

Bibliographic record

VenueCanadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicE-Government and Public Services
Canadian institutionsSheridan College
Fundersnot available
KeywordsAccountabilityThe InternetLocal governmentPublic relationsGovernment (linguistics)Political scienceE-GovernmentPublic administrationInformation and Communications TechnologyBusinessInternet privacyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract Public accountability forums can be useful mechanisms for ensuring that governments are responsive to the perspectives, preferences, and needs of citizens. This study explores how ICTs are affecting public accountability forums and how citizens interact with elected and appointed government officials. A case study of a municipal government in Ontario, Canada, describes how a virtual public accountability forum emerged and functioned based on social media data and interviews with public officials. The case demonstrates that social media can facilitate new channels of interaction between citizens and public officials. Key features of these virtual forums include anonymous participation, variable duration, and dynamic audience size. The case also demonstrates that the demand for information provision within accountability relationships is not just a singular type of ex‐post exchange. There is a new channel of information exchange that is continuous and malleable because it can evolve and change instantaneously over ICTs.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.905
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.009
Scholarly communication0.0010.002
Open science0.0010.000
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 head0.095
GPT teacher head0.321
Teacher spread0.226 · 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; both teacher heads agree on what is shown here.

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

Citations3
Published2022
Admission routes3
Has abstractyes

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