MétaCan
Menu
Back to cohort
Record W1995007333 · doi:10.4018/jmhci.2011010104

Evaluating the Readability of Privacy Policies in Mobile Environments

2011· article· en· W1995007333 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.

Bibliographic record

VenueInternational Journal of Mobile Human Computer Interaction · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsReadabilityComputer scienceComprehensionInternet privacyThe InternetMobile devicePrivacy policyWorld Wide WebMultimediaComputer securityInformation privacy

Abstract

fetched live from OpenAlex

Recent work has suggested that the current “breed” of privacy policy represents a significant challenge in terms of comprehension to the average Internet-user. Due to display limitations, it is easy to represent the conjecture that this comprehension level should drop when these policies are moved into a mobile environment. This paper explores the question of how much does comprehension decrease when privacy policies are viewed on mobile versus desktop environments and does this decrease make them useless in their current format? It reports on a formal subject-based experiment, which seeks to evaluate how readable are privacy policy statements found on the Internet but presented in mobile environments. This experiment uses fifty participants and privacy policies collected from ten of the most popular web sites on the Internet. It evaluates, using a Cloze test, the subject’s ability to comprehend the content of these privacy policies.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.352

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.116
GPT teacher head0.419
Teacher spread0.303 · 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