Time to Unpack the Juggernaut?: Reflections on the Canadian Federal Parliamentary Debates on "Cyberbullying"
Bibliographic record
Abstract
Cyberbullying has come to the fore in federal parliamentary debate largely in the last two years in tandem with high profile media reporting of several teen suicides. The government responded with the Protecting Canadians from Online Crime Act that incorporates, among other things, criminal law responses to nonconsensual distribution of intimate images and gender-based hate propagation, but only at the expense of expanded state surveillance. However, a review of the parliamentary debates reveals a richer array of approaches in which the efficacy of criminal law responses was contested. This article reports on the diversity of viewpoints that emerged within the debates, first contextualizing them within the conceptual complexity of the term “cyberbullying” and the media focus on suicide cases. It suggests that “cyberbullying” has become less a problem and more a political juggernaut for transporting a broad range of issues, as well as ideologies, onto the public agenda. The conceptual elasticity of the term has to some extent facilitated co-optation of tragic suicide cases as a guise for pushing a tough on crime agenda, while obscuring underlying relational and systemic issues repeatedly identified by many claimsmakers within the debates. La cyberintimidation s’est faufilee a l’avant-plan dans les debats parlementaires federaux, surtout au cours des deux dernieres annees, parallelement avec la multiplication d’articles dans de grands medias traitant de nombreux suicides d’adolescents. Le gouvernement a reagi en adoptant le projet de loi C-13, Loi sur la protection des Canadiens contre la cybercriminalite. La loi comporte, entre autres dispositions, des reponses penales a la distribution non consensuelle d’images intimes et a la propagande haineuse fondee sur le sexe, mais uniquement au prix d’une surveillance accrue par l’Etat. Toutefois, un examen des debats parlementaires revele un tableau beaucoup plus varie des facons dont l’efficacite des mesures de droit criminel a ete contestee. L’auteure fait d’abord etat de la diversite des points de vue qui sont ressortis des debats : elle les place d’abord dans le contexte de la complexite conceptuelle du mot « cyberintimidation » et de l’accent mis par les medias sur les suicides. Elle avance que la cyberintimidation est aujourd’hui moins un probleme qu’un veritable mastodonte politique qui englobe un large eventail de questions et d’ideologies pour en faire des enjeux de la politique de l’Etat. L’elasticite conceptuelle du mot a, dans une certaine mesure, favorise la cooptation des suicides tragiques sous pretexte de faire avancer un programme de lutte contre la criminalite tout en masquant les problemes relationnels et systemiques sous-jacents mentionnes a maintes occasions par de nombreux intervenants pendant les debats.
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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 | 0.021 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.100 | 0.048 |
| Scholarly communication | 0.028 | 0.007 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.016 | 0.018 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
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".