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Record W1568611126

The enhanced driver's license: collateral gains or collateral damage?

2012· article· en· W1568611126 on OpenAlexaboutno aff
James M. Clark

Bibliographic record

VenueCalhoun: The Naval Postgraduate School Institutional Archive (Naval Postgraduate School) · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicCybersecurity and Cyber Warfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsComputer securityHomeland securityNexus (standard)Government (linguistics)LicenseCollateralSmart cardNational securityCivil libertiesCollateral damagePolitical scienceIdentification (biology)Identity (music)Internet privacyLawBusinessEngineeringComputer scienceSociologyCriminologyTerrorism
DOInot available

Abstract

fetched live from OpenAlex

On a day-to-day basis, security to most Americans means proving their identity by producing a valid government-issued identification document (ID)most commonly a drivers license. For this reason, terrorists on September 11, 2001, (9/11) placed high value on drivers licenses as a mean to mask preparatory activities leading up to their attack. Congress, as a result, enacted several measures, culminating in the Western Hemisphere Travel Initiative (WHTI), adopted June 1, 2009. The WHTI requires all citizens to show proof of identity while crossing U.S. land, sea, and recently some air borders between Canada, Mexico, the Caribbean, and Bermuda. To facilitate the initiative, the Department of Homeland Security (DHS) expanded on such ongoing ID initiatives as NEXUS, FAST, and SENTRI and adopted a number of different ID solutions, including passport card (PASS Card), Enhanced Drivers License (EDL), Global Entry and the Enhanced Tribal Card while considering others beyond the costly passport to facilitate commerce, trade, and tourism with Border States. All WHTI IDs employ vicinity-read radio frequency identification (RFID) technology, which has raised privacy concerns. This thesis seeks to join the ongoing civil liberties vs. national security debate through a case study of the EDL on both technological and legal grounds.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.518
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0150.006
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.003

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 head0.038
GPT teacher head0.322
Teacher spread0.285 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations0
Published2012
Admission routes1
Has abstractyes

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Same venueCalhoun: The Naval Postgraduate School Institutional Archive (Naval Postgraduate School)Same topicCybersecurity and Cyber Warfare StudiesFrench-language works237,207