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Record W2944154330

Institucionální komunikace v ČR na příkladu Ministerstva vnitra a jeho projektu elektronizace veřejné správy

2012· dissertation· cs· W2944154330 on OpenAlexaboutno aff
Štěpán Soukeník

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2012
Typedissertation
Languagecs
FieldSocial Sciences
TopicPolish Law and Legal System
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsPolitical scienceHumanitiesComputer scienceArt
DOInot available

Abstract

fetched live from OpenAlex

The bachelor's thesis "Institutional Communication in the Czech Republic Focused on Ministry of Interior and the Project Electronisation of Public Administration" targets the specifics of public institutions' marketing communication. The principal objective is to describe major approaches to the theory of institutional communication in different aspects comprising Structural Functionalism, Institutional Economy, Conversational Analysis, Toronto School of Communication Theory and most recent exploratory studies in the theory of social communication and marketing communication in 2011. Based on the broad and narrow context of the terms eGovernment and eDemocracy and taking advantages of the primary and secondary research it analyses two stages of marketing communication campaign of Data Boxes project in 2009, institutionally falling within the Ministry of Interior of the Czech Republic. The thesis consists of the own strategic and tactical concepts and their visual design.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.026
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0040.003
Scholarly communication0.0150.004
Open science0.0010.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0260.005

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 head0.014
GPT teacher head0.271
Teacher spread0.257 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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