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Record W3479330 · doi:10.29173/irie295

Winny and the Pirate Bay: A comparative analysis of P2P software usage in Japan and Sweden from a socio-cultural perspective

2010· article· en· W3479330 on OpenAlexvenueno aff
Kenya Murayama, Thomas Taro Lennerfors, Kiyoshi Murata

Bibliographic record

VenueThe International Review of Information Ethics · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCopyright and Intellectual Property
Canadian institutionsnot available
FundersDivision of Human Resource DevelopmentMinistry of Education, Culture, Sports, Science and Technology
KeywordsIdeologyPerspective (graphical)File sharingContext (archaeology)PoliticsSubject (documents)Dimension (graph theory)SociologySharing economyPolitical scienceLawWorld Wide WebComputer scienceGeography

Abstract

fetched live from OpenAlex

In this paper, we examine the ethico-legal issue of P2P file sharing and copyright infringement in two different countries – Japan and Sweden – to explore the differences in attitude and behaviour towards file sharing from a socio-cultural perspective. We adopt a comparative case study approach focusing on one Japanese case, the Winny case, and a Swedish case, the Pirate Bay case. Whereas similarities in attitudes and behaviour towards file sharing using P2P software between the two countries are found in this study, the Swedish debate on file sharing has been coloured by an ideological and political dimension, which is absent in the Japanese context. This might indicate that Swedes have been more interested in issues of right and wrong, and the creation of political subject of piracy, while the Japanese are more interested in their own individual well being.

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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0030.003
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.048
GPT teacher head0.321
Teacher spread0.274 · 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

Citations3
Published2010
Admission routes1
Has abstractyes

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