Bibliographic record
Abstract
In recent years the Internet, or cyberspace, has become an increasingly important part of everyday life for a growing proportion of the world's population. Although at present the demographic of Internet usage in Germany remains predominantly male, educated, under forty, and Western, this is beginning to change. A recent Focus article suggested, for example, that more and more women are now using the Internet (Focus Online). However, the most rapidly changing aspect of Internet usage in Germany seems to be the increasing number of East Germans who are going online. As an article in 2002 in Spiegel put it, Langsam, aber sicher holt der Osten digital auf. Based on the findings of the DENIC agency, Spiegel reported that the number of World Wide Web (WWW) addresses registered in the new Lander was up by 50% in 2001, whereas elsewhere in Germany the number sank by up to 20% (Aufhholjagd bei De-Domains). One of the effects of this increased usage of the Internet by East Germans has been a growing number of Web pages dealing East German issues and in particular the question of how to deal with the GDR period. This development, however, has been greeted a degree of alarm by some members of the p ress. The most prominent writer in Germany on this topic is the journalist Henryk M. Broder. In his usual polemical manner, Broder follows a popular conception of the Internet as a potentially dangerous Wild West populated by sexual deviants and political extremists, in which the normal rules of civilization do not apply and from which the vulnerable members of society must be protected (Miller 57). Broder's articles tend towards an image of the Web as being almost taken over by extremist East German cells. He even refers to sites where one can ostensibly rearm for any coming revolution, buying Eine Kalaschnikow fur 98 Euro (Eine Kalaschnikow). Elsewhere he suggests that, as well as giving extremist fringe voices a platform, German society's response to Internet usage by some East Germans seems to turn normal values of justice on their head. He reports, for example, the case of Mario Falcke, a former victim of the Stasi who now runs the Website Stasiopferde and who was threatened legal action for including a link to a site that published a list of Stasi members: Der Berliner Datenschutzbeauftragte interveniert zu Gunsten ehemaliger Stasi-Mitarbeiter und setzt ein Opfer des DDR-Regimes unter Druck, the article claims (Broder, Empfindliche Strafen). Leaving aside the rights and wrongs of this
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".