A New Method to Address Cyberbullying in the United States: The Application of a Notice-and-Takedown Model as a Restriction on Cyberbullying Speech
Notice bibliographique
Résumé
TABLE OF CONTENTS I. INTRODUCTION 121 II. THE PROBLEM OF CYBERBULLYING AND THE NEED FOR A LEGAL SOLUTION 123 III. STATE RESPONSES TO CYBERBULLYING AND LEGISLATIVE SHORTCOMINGS 125 A. The United States' Response to Cyberbullying Has Occurred a the State Level at the State Level 126 B. Criticism of State Cyberbullying Responses and the Need for National Action 126 IV. THE RIGHT TO BE FORGOTTEN AS A POTENTIAL RESPONSE TO CYBERBULLYING AND WHY IT LIKELY WILL NOT SURVIVE FIRST AMENDMENT SCRUTINY IN THE UNITED STATES 127 A. The Right to be Forgotten, Criticisms of the Right, and Its Impact on Speech in the E.U. 128 B. The Right to be Forgotten, as Implemented in Europe, Would Face Serious First Amendment Challenges in the United States 129 1. Low-Value Speech Can Be Restricted by the Government with Minimal First Amendment Scrutiny 130 2. Restrictions on Speech That Is Not Low-Value Are Subject to Strict Scrutiny Under the First Amendment 131 C. Due to Its Chilling Effect on the Content of a Wide Range of Speech, the Right to Be Forgotten Is Not Likely to Survive Strict First Amendment Scrutiny in the United States 133 V. POLICYMAKERS SHOULD LOOK TO THE NOTICE-AND-TAKEDOWN PROCEDURES OF THE DIGITAL MILLENNIUM COPYRIGHT ACT, WHICH MAY PROVIDE A CONSTITUTIONAL MEANS FOR RESTRICTING THE CONTENT OF SPEECH 134 A. Background on the DMCA and Its Notice-and-Takedown Provisions 134 B. The Argument That the DMCA's Notice-and-Takedown Procedures Provide for a Potentially Unconstitutional Restriction of Speech 136 VI. APPLICATION OF THE DMCA NOTICE-AND-TAKEDOWN MECHANISM AS AN ALTERNATIVE MODEL TO RESTRICT THE CONTENT OF CYBERBULLYING SPEECH 137 A. The Elements of This Proposed Notice-and-Takedown Mechanism 138 B. Why This Mechanism Is a Constitutional Speech Restriction 139 C. Potential Counterarguments and the Need for Further Scholarship 141 1. Websites Already Have Protections in Place 141 2. The Need for an Appeals Process 142 VII. CONCLUSION 143 I. INTRODUCTION Ghyslain Raza. His story is one many may not want to remember--but should never forget. One day, while at school in Quebec, Canada, Raza was going about his day like any typical 14-year-old. He had countless things to look forward to: spending time with friends, high school, and enjoying what are supposed to be some of the best years of life. His teenage innocence, however, was about to be ripped away from him far too soon. As part of a school project, Raza entered a television studio at his school and had someone film him reenacting a lightsaber scene from Star Wars. Raza submitted the seemingly harmless and inconsequential video in his class and then went on with his life. (1) A year later, the video was posted on YouTube, without Raza's consent, and quickly went viral. Within days of its posting, the video was well on its way to becoming the most popular Internet video of all time. But rather than enjoying his newfound celebrity, Raza was faced with a massive cyberbullying onslaught from people he did not know. (2) What I saw was mean. It was violent. People were telling me to commit Raza said of the video's release. (3) Raza further commented that no matter how hard I tried to ignore the people telling me to commit suicide, I could not help but feel worthless, like my life was not worth living. …
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,004 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».