MétaCan
Menu
Back to cohort
Record W2049459183 · doi:10.1145/1572532.1572534

Revealing hidden context

2009· article· en· W2049459183 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInternet Traffic Analysis and Secure E-voting
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFirewall (physics)Computer scienceContext-based access controlApplication firewallHuman–computer interactionMental stateComputer securityStateful firewallPsychologyCognitive science

Abstract

fetched live from OpenAlex

The Windows Vista personal firewall provides its diverse users with a basic interface that hides many operational details. However, concealing the impact of network context on the security state of the firewall may result in users developing an incorrect mental model of the protection provided by the firewall. We present a study of participants' mental models of Vista Firewall (VF). We investigated changes to those mental models and their understanding of the firewall's settings after working with both the VF basic interface and our prototype. Our prototype was designed to support development of a more contextually complete mental model through inclusion of network location and connection information. We found that participants produced richer mental models after using the prototype than when working with the VF basic interface; they were also significantly more accurate in their understanding of the configuration of the firewall. Based on our results, we discuss methods of improving user understanding of underlying system states by revealing hidden context, while considering the tension between complexity of the interface and security of the system.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.224

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.015
GPT teacher head0.241
Teacher spread0.226 · 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