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Record W3173712982 · doi:10.29173/irie343

Funktionen, Probleme und Regulierung von Suchmaschinen im Internet

2005· article· de· W3173712982 on OpenAlexvenueno aff
Christoph Neuberger

Bibliographic record

VenueThe International Review of Information Ethics · 2005
Typearticle
Languagede
FieldBusiness, Management and Accounting
TopicDigital Innovation in Industries
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Suchmaschinen haben eine Orientierungs- und Speicherfunktion im Internet. Der Wettbewerb zwischen Google, Yahoo und Microsoft, der im Jahr 2004 an Schärfe gewonnen hat, wird als „Krieg der Architekturen“ interpretiert, bei dem es letztlich darum geht, allgemeine Standards für die Aufbereitung und Suche digitaler Informationen zu setzen. Die Frage, wie groß der Einfluss des Marktführers „Google“ auf die Aufmerksamkeitslenkung im Internet ist, lässt sich noch nicht abschließend beantworten. Gegen ein „Googlepol“ spricht zum Beispiel, dass viele Nutzer parallel auch bei anderen Anbietern suchen. Die Qualität der SuchmaschinenErgebnisse wird nicht nur durch technische Schwächen, sondern in wachsendem Maße auch durch externe und interne Formen der Manipulation beeinträchtigt. In der letzten Zeit haben sich Suchmaschinen-Betreiber und Suchmaschinen-Optimierer in Selbstverpflichtungserklärungen auf Regeln geeinigt, durch die mehr Transparenz für die Nutzer geschaffen und das Problem des „Spamming“ von Suchmaschinen gelöst werden soll.

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)0.010
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0030.018
Scholarly communication0.0130.015
Open science0.0010.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.043
GPT teacher head0.309
Teacher spread0.266 · 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 designNot applicable
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

Citations1
Published2005
Admission routes1
Has abstractyes

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