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Record W1556840283 · doi:10.22230/cjc.2011v36n1a2252

Interpreting Privacy on Campus: The Freedom of Information and Personal Privacy and Ontario Universities

2011· article· en· W1556840283 on OpenAlexaffvenueabout
Martin Dowding

Bibliographic record

VenueCanadian Journal of Communication · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicLaw, Rights, and Freedoms
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsLegislationPrivacy laws of the United StatesPrivacy policyInformation privacyPolitical scienceInternet privacyPrivacy lawInformation privacy lawPersonally identifiable informationPublic relationsAcademic freedomSociologyHigher educationLawComputer science

Abstract

fetched live from OpenAlex

When the Freedom of Information and Protection of Privacy Act (FIPPA) was imposed on Ontario’s university campuses in 2006, faculty and students were made to look closely at their own habits and to reconsider campus traditions relating to privacy. The backdrop to the legislation is a complex matrix of campus relations, policy, sharing of health information, and the use and abuse of information and communication technologies. Part 1 of this article examines the recent history of privacy in general and privacy on campus in Ontario, Canada, and the United States. Part 2 reports the outcome of a series of focus groups held on two Ontario university campuses in which faculty and undergraduate students were asked about their perceptions of privacy on campus and their knowledge and comprehension of FIPPA.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.970
Threshold uncertainty score0.961

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0380.051
Scholarly communication0.0150.008
Open science0.0020.008
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.022
GPT teacher head0.228
Teacher spread0.206 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations5
Published2011
Admission routes3
Has abstractyes

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