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Record W1812050345 · doi:10.1109/cscwd.2001.942238

Towards distributed privacy for CSCW

2002· article· en· W1812050345 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
TopicDigital Rights Management and Security
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsComputer-supported cooperative workComputer scienceCertificationCollaborative softwareAuthentication (law)Field (mathematics)Work (physics)Computer securityWorld Wide WebEngineering

Abstract

fetched live from OpenAlex

Tools for computer supported collaborative work offer many advantages for their users. Some developments in this field have included agent-based approaches for CSCW. Many challenges face the development and application of distributed, agent-based solutions for CSCW. A concern often overlooked is the acceptability and social impact of these technologies. In particular, the management of the privacy of collaborators is a paramount issue that must be accommodated. Included and related to the privacy of user information and interactions are assurances of integrity, certification, validation, ownership, non-repudiation, and authentication of individuals and software systems operating on disparate computers and operating systems, communicating over heterogeneous networks. We outline our early work on an approach for accountable privacy that may be applied to distributed computer supported cooperative work (CSCW) environments. Particular challenges for the issue of privacy associated with the CSCW application scenario are discussed.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.959
Threshold uncertainty score0.264

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 communication0.0000.001
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 head0.036
GPT teacher head0.239
Teacher spread0.203 · 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

Quick stats

Citations3
Published2002
Admission routes1
Has abstractyes

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