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Record W2944651552 · doi:10.7202/1058474ar

Storing Authenticity at the Surface and into the Depths: Securing Paper with Human- and Machine-Readable Devices1

2019· article· en· W2944651552 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueIntermédialités Histoire et théorie des arts des lettres et des techniques · 2019
Typearticle
Languageen
FieldComputer Science
TopicUser Authentication and Security Systems
Canadian institutionsUniversité de Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCovertReadabilityComputer scienceAuthentication (law)Space (punctuation)Computer securityHuman–computer interactionInternet privacyMultimedia

Abstract

fetched live from OpenAlex

This article examines the media technologies that mark paper as authentic. Using the examples of passports and paper banknotes, it considers the security features (e.g. graphic marks, holographs, chips) that do the work of reliably storing, protecting, and communicating authenticity across both space and time. These overt and covert authentication devices are examined in two interconnected ways: 1) as technologies with specific temporal conditions, constrained both by technical longevity and functional lifespan; and 2) as technologies that must be continuously reinvented to outpace counterfeiters and forgers. Together, these attributes have led to strategies of concealment that shift authentication from a human-legible activity at the perceptible surface to one that is concealed in the depths of machine readability. While this adds a level of security, it is also an example of how the material environment becomes rich in information that is inaccessible to human processing.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.746
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.276
Teacher spread0.253 · 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