Bibliographic record
Abstract
The study of the relationship between the Internet and democracy has produced two main debates. Some studies have said that the Internet has significantly contributed to democracy while others disagree. This study challenged the thesis of Habermas (2006) about the relationship between the Internet and Deliberative Democracy. This study was built on the following propositions: that the Internet causes bloggers to become parasitic, fragmented, and isolated; that it is effective in breaking down authoritarian regimes to create an egalitarian relationship, but it fails as a deliberative medium. This study used the concept of the public sphere and Habermas’ Deliberative Democracy (2006). It also explored the use of 2.0 qualitative methods with a hacking analysis perspective. Moreover, it gained data from the Internet by using the latest version of 2.0 Web and a virtual community. It focused on both discursive and non-discursive construction. The results of this study support only one of Habermas’ three propositions: that the Internet creates egalitarianism. Thus, this study rejects Habermas’ thesis apart from this one proposition. Furthermore, this study recommends that further research be done using the same propositions but on Twitter instead of the Internet.
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 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
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".