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Record W4234238019 · doi:10.32920/ryerson.14664693

Senior leaders' use of web 2.0 and social media in the Ontario Public Service

2021· preprint· en· W4234238019 on OpenAlexaffabout
Anne Bermonte

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsToronto Metropolitan UniversityToronto Public Health
Fundersnot available
KeywordsPublic relationsTransparency (behavior)Social mediaBureaucracyGovernment (linguistics)Public serviceThe InternetIntranetBusinessPolitical scienceSociologyWorld Wide WebPolitics

Abstract

fetched live from OpenAlex

The majority of the literature on Web 2.0 and social media describes several public administration benefits: building trust, achieving transparency, recruiting young professionals and realizing efficiencies. The literature argues that leadership is required to bring in cultural changes to support the use of web-based tools and links familiarity with successful adoption. Yet, little research exists exploring how these issues influence senior leaders' use of Web 2.0 and social media in a government bureaucracy. This study uses a mixed methods approach to look at senior leaders use and adoption patterns in the Ontario public service, to probe the concept of familiarity by understanding the relationship between home/personal use and work/professional use, and to contribute to an emerging public administration area. An assessment of government of Ontario Internet and intranet sites, an analysis of survey responses from 117 senior leaders in the OPS and information gathered from interviews support the study's findings.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.682
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.366
GPT teacher head0.405
Teacher spread0.039 · 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

Citations3
Published2021
Admission routes2
Has abstractyes

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