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Record W2143520620 · doi:10.2202/1944-2866.1125

Overcoming the Warez Paradox: Online Piracy Groups and Situational Crime Prevention

2011· article· en· W2143520620 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePolicy & Internet · 2011
Typearticle
Languageen
FieldComputer Science
TopicCybercrime and Law Enforcement Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsSituational ethicsConstruct (python library)Focus groupLaw enforcementEnforcementPrestigeCriminologyProcess (computing)SanctionsInternet privacyWork (physics)PsychologyBusinessComputer securitySocial psychologyPublic relationsLawSociologyPolitical scienceComputer scienceEngineeringMarketing

Abstract

fetched live from OpenAlex

Abstract US federal law enforcement operations occurring between 2001 and 2005 attempted to disrupt the online piracy scene, targeting copyright piracy rings known as ‘warez groups’. Previous work on warez groups has demonstrated a paradoxical situation where attempts to curtail warez group activities through policing and advancements in DRM only further encourage such groups to crack and distribute content. This study collected data on 93 convictions from these policing operations to construct a crime script of these groups' motivations and modus operandi in the release process. The results confirm previous findings that attempts to disrupt the activities of warez groups are counterproductive. To avoid the paradox, this study suggests that industry account for the motivations and modus operandi of these groups by creating DRM technologies which allow un‐cracked content to seep through the testing step of the script, thereby placing a group's ability to obtain prestige at risk. Law enforcement should focus on apprehending crackers, as they are the most significant step in the release process.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.776
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.067
GPT teacher head0.307
Teacher spread0.240 · 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