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Data Protection Laws on Publicly Available Data

2018· article· en· W2959893803 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInstitute for Legal Studies Chonnam National University · 2018
Typearticle
Languageen
FieldHealth Professions
TopicInnovation in Digital Healthcare Systems
Canadian institutionsnot available
Fundersnot available
KeywordsData 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

Abstract

fetched live from 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.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.831
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.003
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.611
GPT teacher head0.503
Teacher spread0.108 · 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