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Record W1876813795

Do Not Dismiss ‘Adequacy’: European Data Privacy Standards are Entrenched

2012· article· en· W1876813795 on OpenAlexaboutno aff
Graham Greenleaf

Bibliographic record

VenueSSRN Electronic Journal · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Criminal Justice and Data Protection
Canadian institutionsnot available
Fundersnot available
KeywordsDirectivePolitical scienceData Protection DirectiveMember statesLawData Protection Act 1998European unionInternational tradeLaw and economicsBusinessEuropean Union lawEconomics
DOInot available

Abstract

fetched live from OpenAlex

The ‘adequacy’ mechanism in the EU data protection Directive, and perceptions of it, have been one (but only one) of the means by which the influence of European data privacy standards have been felt outside Europe. The EU’s ‘border control’ approach is to require member states to limit data exports unless ‘adequate protection’ can be demonstrated at the receiving end (EU Directive Articles 25, 26). There are now 81 jurisdictions in the world with data privacy laws, excluding those only covering the public sector (Greenleaf, 2011b), so there are 53 theoretical candidates for adequacy findings. However, the EU has only made adequacy decisions in relation to nine jurisdictions as a whole (Andorra, Argentina, Canada, Switzerland, Faroe Islands, Guernsey, Israel, Isle of Man, and Jersey), some of which are of relatively little economic or political significance. ‘Adequacy’ certainly has its critics, and many criticisms, theoretical and practical, have substance. But this article argues that we should not be too hasty, and outlines a number of reasons why ‘adequacy’ is now so entrenched in legal systems across the world that it will not be easy to remove. The list of countries considered adequate is expanding slowly: Uruguay and New Zealand will soon be added to the list. Despite the slow pace of the EU in making and publicising assessments, the desire to eventually obtain an ‘adequacy’ finding from the EU, or in a more amorphous form, to have one’s law regarded as of the highest international standard (that the EU Directive is considered by many to embody) has been a significant influence on the development of laws outside Europe. Consideration of the 29 African, Latin American, Asian, Australasian, and other jurisdictions with data privacy laws suggests that the EU Directive is the most significant overall influence on the content of data privacy laws outside Europe, and that its influence is gradually strengthening.As a result, ‘adequacy’ has stopped being a primarily EU concept. Outside Europe, ‘border control’ data export limitations are found in almost all (25/29) data privacy laws in all regions, though their strength varies a great deal, and they are not yet in force in the laws of Malaysia and Hong Kong. Non-EU/EEA European countries also have data export limitations in their law because of the Additional Protocol to Council of Europe Convention 108. So anyone who wishes to criticise the EU for wanting to ‘impose its standards on the rest of the world’ had better level the same accusation at the rest of the world.There is also, as yet, little indication that the current revisions of the Directive or the Convention will result in Europe abandoning its ‘border control’ approach. The future for European privacy standards, including the ‘border control’ principle of ‘adequacy’ is far more positive than the criticisms they receive might lead us to believe. Attempts to replace the adequacy concept with some notion of ‘accountability’ that abandons ‘border control’, not only goes against the likely direction of reforms of the Directive, but would also involve changing the Council of Europe Convention Additional Protocol, and all non-EU/EEA laws, and almost all data privacy laws outside Europe as well. The inertia that exists against such change occurring is considerable. Like it or loath it, adequacy may be here to stay.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.081
metaresearch head score (Gemma)0.175
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.081
Threshold uncertainty score0.428

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0810.175
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0060.041
Scholarly communication0.0220.039
Open science0.0030.016
Research integrity0.0140.029
Insufficient payload (model declined to judge)0.0030.002

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 head0.069
GPT teacher head0.351
Teacher spread0.282 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreCommentary

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

Citations1
Published2012
Admission routes1
Has abstractyes

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