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Record W4251794571 · doi:10.15353/cgjsc.v5i1.3741

Publication Bans in a Facebook Age: How Internet Vigilantes Have Challenged the Youth Criminal Justice Act’s “Secrecy Laws” Following the 2011 Vancouver Stanley Cup Riot

2016· article· en· W4251794571 on OpenAlexvenueaboutno aff
Tania Arvanitidis

Bibliographic record

VenueCanadian Graduate Journal of Sociology and Criminology · 2016
Typearticle
Languageen
FieldComputer Science
TopicHate Speech and Cyberbullying Detection
Canadian institutionsnot available
Fundersnot available
KeywordsThe InternetSecrecyCriminologyEconomic JusticeSocial mediaPolitical scienceShameLawCriminal justiceInternet privacyAnonymitySociologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

On June 15th, 2011, a hockey riot occurred in Vancouver, British Columbia. This event is prominent in Canada’s history for, among other reasons, the unprecedented extent to which it was documented via photographs and video footage. The days that followed the riot saw much of this media documentation uploaded to social media platforms on the Internet, where Internet users worked together to identify and collectively “name and shame” those believed to have been involved in the disturbance. Several individuals targeted by these “Internet vigilantes” were young offenders whose identities are legally protected from publication under the Youth Criminal Justice Act (YCJA). This article examines the phenomenon of “Internet vigilantism”, and raises the issue of whether those provisions within the YCJA that prohibit the identification of youth remain relevant today, given the current difficulties in enforcing these provisions. Following an overview of these “secrecy provisions”, the phenomenon of Internet vigilantism is defined, and challenges posed by acts of Internet vigilantism are discussed. A “naming and shaming” Facebook group created for the purpose of identifying participants in the 2011 Vancouver riot is then looked to as a case study of Internet vigilantism in action. This article concludes with recommendations for how justice officials and social media outlets may modify current practices to better protect the safety and security of young offenders, and to minimize harmful instances of Internet vigilantism. Le 15 juin 2011, une émeute liée au hockey s’est déroulée à Vancouver, en Colombie-Britannique. Cet événement est important dans l’histoire du Canada, entre autres raisons, pour sa documentation sans précédent par l’entremise de photographies et de séquences vidéos. Les jours qui ont suivi l’émeute, une grande quantité d’information médiatique a été téléchargée sur les médias sociaux, où des internautes collaboraient afin d’identifier et de « nommer et pointer du doigt » ces personnes qui auraient participé aux troubles sociaux. Plusieurs individus ciblés par ces « justiciers de l’Internet » étaient de jeunes contrevenants dont l’identité est légalement protégée contre la publication en vertu de la Loi sur le système de justice pénale pour les adolescents (LSJPA). Cet article se penche sur le phénomène des « justiciers de l’Internet » et s’interroge sur la pertinence actuelle des dispositions dans le cadre de la LSJPA qui interdisent l’identification des jeunes, étant donné les difficultés présentes à faire respecter ces dispositions. Après un aperçu de ces « dispositions relatives au secret », le phénomène des justiciers de l’Internet est défini, et les défis posés par leurs actions sont discutés. Le groupe Facebook qui visait à « nommer et pointer du doigt » les participants de l’émeute de 2011 de Vancouver est présenté ici comme une étude de cas sur les justiciers de l’Internet. Cet article formule des recommandations sur la façon dont les fonctionnaires de la justice et les médias sociaux peuvent modifier les pratiques courantes afin de mieux protéger la sécurité des jeunes délinquants et réduire au minimum les effets nuisibles découlant des actions des justiciers de l’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 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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.264
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.100
GPT teacher head0.258
Teacher spread0.159 · 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 teacher head, 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
Published2016
Admission routes2
Has abstractyes

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Same venueCanadian Graduate Journal of Sociology and CriminologySame topicHate Speech and Cyberbullying DetectionFrench-language works237,207