MétaCan
Menu
Back to cohort
Record W97126409

What to Do about Question Period: A Roundtable

2010· article· en· W97126409 on OpenAlexvenueno aff
Michael Chong, Marlene Jennings, Mario Laframboise, Libby Davies, Tom Lukiwiski

Bibliographic record

VenueCanadian parliamentary review · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCommonwealth, Australian Politics and Federalism
Canadian institutionsnot available
Fundersnot available
KeywordsThursdayConventionLawPrime ministerPeriod (music)ScheduleOrder (exchange)DecorumParliamentPolitical scienceOperations researchPublic administrationSociologyManagementPoliticsHistoryTheologyEconomicsArtPhilosophyMathematicsFinance
DOInot available

Abstract

fetched live from OpenAlex

On May 7, 2010 a motion calling for the Standing Committee on Procedure and House Affairs to recommend changes to the Standing Orders and other conventions governing Oral Questions was introduced by the member for Wellington–Halton Hills. Among other things the Committee would consider ways of (i) elevating decorum and fortifying the use of discipline by the Speaker, to strengthen the dignity and authority of the House, (ii) lengthening the amount of time given for each question and each answer, (iii) examining the convention that the Minister questioned need not respond, (iv) allocating half the questions each day for Members, whose names and order of recognition would be randomly selected, (v) dedicating Wednesday exclusively for questions to the Prime Minister, (vi) dedicating Monday, Tuesday, Thursday and Friday for questions to Ministers other than the Prime Minister in a way that would require Ministers be present two of the four days to answer questions concerning their portfolio, based on a published schedule that would rotate and that would ensure an equitable distribution of Ministers across the four days. The motion was debated on May 27, 2010. The following extracts are taken from that debate.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.495
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.358
Teacher spread0.322 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations3
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueCanadian parliamentary reviewSame topicCommonwealth, Australian Politics and FederalismFrench-language works237,207