MétaCan
Menu
Back to cohort
Record W2188949668

University of Calgary properly withheld some information but improperly withheld other information

2011· article· en· W2188949668 on OpenAlexaboutno aff
Wayne Wood

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsnot available
Fundersnot available
KeywordsDutyFreedom of informationLawInternet privacyPolitical scienceBusinessComputer science
DOInot available

Abstract

fetched live from OpenAlex

An Adjudicator with the Office of the Information and Privacy Commissioner has determined that the University of Calgary properly withheld some information that had been requested by an individual, but that it improperly withheld other information and failed to meet its duty to assist. The Applicant, a former employee of the U of C, requested information held by other employees, a Wellness Centre and a doctor associated with the Wellness Centre. The Public Body provided some information to the Applicant, but withheld other information, citing several sections of the Freedom of Information and Protection of Privacy Act (FOIP). The Public Body did not provide information from the Wellness Centre or the doctor, instead advising the Applicant to request those records directly from the Wellness Centre. Following an inquiry into the matter, Adjudicator Wade Riordan Raaflaub determined the Public Body properly withheld some information, but he ruled the Public Body did not properly apply some sections of FOIP and ordered the Public Body to release that information. Riordan Raaflaub found the Public Body failed to meet its duty to assist the Applicant, as it failed to make every reasonable effort to search for the requested records and/or inform the Applicant about the search. He found the Public Body had no duty to search for and provide records from the Wellness Centre, with one exception.

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)0.016
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.605
Threshold uncertainty score0.785

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.047
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0210.010
Scholarly communication0.0210.004
Open science0.0040.006
Research integrity0.0240.019
Insufficient payload (model declined to judge)0.0240.008

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 head0.023
GPT teacher head0.214
Teacher spread0.192 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2011
Admission routes1
Has abstractyes

Explore more

Same topicPrivacy, Security, and Data ProtectionFrench-language works237,207