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Enregistrement W2959893803 · doi:10.38133/cnulawreview.2018.38.2.1

Data Protection Laws on Publicly Available Data

2018· article· en· W2959893803 sur OpenAlexaboutno aff
Kyung Sin Park

Notice bibliographique

RevueInstitute for Legal Studies Chonnam National University · 2018
Typearticle
Langueen
DomaineHealth Professions
ThématiqueInnovation in Digital Healthcare Systems
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésData Protection Act 1998Personally identifiable informationInternet privacyInformation privacy lawInformation privacyPrivacy laws of the United StatesPrivacy lawGermanRight to privacyPolitical scienceSupreme courtNorm (philosophy)LawBusinessPrivacy policyComputer securityPrivacy by DesignComputer scienceGeography

Résumé

récupéré en direct d'OpenAlex

광의의 프라이버시 즉 공개의 정도에 관계없이 모든 개인정보를 보호대상으로 삼는개인정보보호법과 개인정보자기결정권의 실제 발전연혁을 살펴보면 협의의 프라이버시 즉 ‘정보감시로부터의 자유’를 더욱 적극적으로 보호하기 위해 고안된 ‘정보소유권론’의 자연스러운 전개라고 할 수 있다. 즉 사물(정보)과 사람의 관계를 정보의 내용이나 유통연혁에 관계없이 일괄적으로 설정함으로서 힘없는 개인이 기업이나 정보에 정보제공을 하면서 겪을 수 있는 정보감시를 막기 위한 것이었다. 이렇게 개인정보보호법/자기결정권을 개념화할 경우 협의의 프라이버시 법익이 존재한다고 볼 수 없는 일반적 공개가 이루어진 정보들에 대해서는 일괄적으로 개인정보보호법/자기결정권이 적용되지 않는 것이 옳다. 이미 일반적으로 공개된 개인정보의 경우 추가적으로 발생할정보감시에 의한 위축효과가 존재하지 않기 때문이다. 호주, 캐나다, 독일(2017년 7월이전), 싱가포르, 대만은 강력한 개인정보보호법을 가지고 있으면서도 일반적으로 공개된 정보에 대해서는 예외를 두고 있다. 우리나라도 2016년 8월 대법원 판결에서 ‘일반적으로 공개된 정보’에 대해서는 예외를 인정한 바 있다. 일반적으로 공개된 정보를 사안별로 ‘원칙적 보호 예외적 허용’ 프로세스를 거치도록하는 것도 표현의 자유와 알 권리에 불필요한 입증책임을 부가하는 것이다. 단어의 의미가 다른 단어와의 관계 속에서만 성립될 수 있듯이 한 사람의 정체성 역시 다른 사람들과의 관계 속에서만 성립된다. 학생들 모르게 교수가 있을 수 없고 의뢰인 모르게 변호사가 있을 수 없다. 그런 관계 속에서는 그 관계를 형성하는 정보의 공유는 예외가아니라 원칙이 되어야 한다. 그렇다면 사회 전체의 구성원들의 상호관계를 가능케 하는정보공유도 필요한데 바로 이것이 ‘일반적으로 공개된 정보’의 예외이다.There are two conflicting trends in privacy. The broader sense of privacy, captured in the German concept of personality right, protects all information about a person in principle and allows others to use or share the information about others only when certain legitimate need or public interest in doing so is recognized. Such privacy is gaining traction around the world as people are depending on more and more third parties in communicating with one another, exposing themselves to greater risk of surveillance. The narrower sense of privacy is represented by an American norm against intrusion into or public disclosure of private spaces or private facts. We have thought that data protection law and the right to informational self-determination are solely based on the broader concept of privacy. However, the concepts’ genealogy shows that they were developed as tools to protect the narrower concept of privacy. It was a natural development of ‘data ownership right’ which established people-to-information relationship en gross regardless of the contents and other aspects of the data concerned, so as to protect powerless individuals engaged in data transactions with powerful companies and governments. Understood this way, the information that has been legally made available to the public should not be protected by data protection laws. Indeed, Australia, Canada, pre-GDPR Germany, Singapore, Taiwan, etc., have strong data protection law and yet provide for exceptions to publicly available data. The Korean Supreme Court in 2016 also recognized such exception. Notwithstanding such genealogy, one may argue for the broader sense of privacy as an default rule which allows use of publicly available data only on proof of public interest but such rule unnecessarily suppresses the pluralistic ideal that freedom of speech pursues. The meanings of words are found only in relation to other words. One’s identity is built only in relation to other persons. There cannot be a professor without students. There cannot be an attorney without clients. Within those relationships, personal data necessary for sustenance of those relationship are by default free to be shared and used without any additional proof. There must be information necessary for sustenance of relationship among all people in the community, and that is publicly available information.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,049
score de la tête « metaresearch » (Gemma)0,191
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,049
Score d'incertitude au seuil0,261

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0490,191
Méta-épidémiologie (sens strict)0,0010,002
Méta-épidémiologie (sens large)0,0020,003
Bibliométrie0,0050,009
Études des sciences et des technologies0,0050,011
Communication savante0,0160,013
Science ouverte0,0050,010
Intégrité de la recherche0,0170,015
Charge utile insuffisante (le modèle a refusé de juger)0,0300,026

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.

Tête enseignante Opus0,611
Tête enseignante GPT0,503
Écart entre enseignants0,108 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2018
Routes d'admission1
Résumé présentoui

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