Content analysis of new means of communication in contemporary democratic states
Bibliographic record
Abstract
The previous period of United States presidential elections of 1996 has redirected the relevant scientific research to investigate the correlation online communication - political sphere. Consequently were formulated various paradigms and the most discussed was the democratic paradigm, according to which the representation serve as a basic principle of modern democracy. The study of the level of influence of new communication technologies on political sphere became, for a number of scientific investigations carried out in USA, Canada and later in some European countries such as France, Italy, the UK (in 2000 and since 2007 in Romania), an important objective of empirical research. In most cases, the first stage of the investigation of online political communication has been marked by some methodological problems such as: the changeable nature of web space, the necessity to elaborate new indicators able to represent basic aspects of studied reality, the temporal validity of the data. The elaboration of A Model of Cyber –Interactivity by Sally J. McMillan has contributed to overcome these difficulties and has demonstrated the effectiveness of content analysis as research method used for the study of Web Space dynamic reality. Later, the research team from the University of Rochester (Paul Ferber, Frantz Foltz, Rudy Pugliese) have perfected the two-way interactivity model (elaborated by Sally J. McMillan) and have it completed with three-dimensional model of interactivity for the purpose of quantitative investigation of political websites and to argue that these forms of new media correspond to the ideals of cyberdemocracy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".