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Identity Cards and Identity Romanticism

2008· book-chapter· en· W2282413001 on OpenAlexaboutno aff
A. Michael Froomkin

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicLaw, Rights, and Freedoms
Canadian institutionsnot available
Fundersnot available
KeywordsNational identityExceptionalismPolitical scienceRomanceIdentity (music)ComityLawMedia studiesSociologyPoliticsAestheticsArtLiterature

Abstract

fetched live from OpenAlex

Abstract “National ID cards” are scare words in the United States, in England, and to a degree throughout the common-law world. If the instinctively negative reaction to ID cards were only an American phenomenon, one might dismiss it as yet another example of American exceptionalism—or, perhaps, another example of the U.S. failure to learn from foreign experience. But this powerful popular distaste for government-issued ID cards is not limited to the U.S. Similar and powerful reactions are found in England, Australia, and Canada. Indeed, in 2000, one could say that only four common-law countries had adopted ID cards in peacetime: Cyprus, Hong Kong, Malaysia, and Singapore. Meanwhile, however, ID cards are a routine and often uninteresting fact of life in the democracies of the civil-law world. That difference deserves exploration. (Some might argue that ID cards are inescapable, and that even the U.S. has them although it does not admit it, but this makes the difference in popular attitudes even more difficult to understand.) This chapter suggests that the U.S. hostility to ID cards is based on a romantic vision of free movement, and that the English view is tied to a related concept of “the rights of Englishmen.” I then suggest that these views distract from the real issues raised by contemporary national ID plans in the common and civil-law worlds. Today’s issues, I suggest, involve a complex set of data protection issues that have little to do with romantic stories of cowboys and motorists talking back to policemen, and a great deal to do with data storage and access.

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 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)0.000
metaresearch head score (Gemma)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.649
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.011
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.292
Teacher spread0.261 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations5
Published2008
Admission routes1
Has abstractyes

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