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Record W201203918

Observations on the theory and practice of Parliamentary Government

2008· article· en· W201203918 on OpenAlexvenueno aff
Ashley Cochran, Heather Cochran

Bibliographic record

VenueCanadian parliamentary review · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsLegislaturePoliticsLegislatorDemocracyConversationPolitical scienceLawReading (process)SociologyPublic administrationMedia studiesLegislation
DOInot available

Abstract

fetched live from OpenAlex

“Well, I guess that’s why it’s called Question Period, not Answer Period!” By the end of our term as interns at the British Columbia Legislature, this phrase had become a common refrain among both participants and observers of the daily Question Periods. As recent Political Science Graduates and rookies to the legislative scene, however, the quip was of more than a passing interest. It spoke to what we found most shocking – and most frustrating – about our first hand experience of our system of parliamentary democracy. In our first year Political Science classes we learned that parliaments were “talking places” – the buildings in which first nobility, and then elected officials, developed solutions to public policy problems and debated the issues of the day – and of course the odd scandal too. While this may be a simplified and perhaps optimistic reading of the function of legislatures, it is also the reading which informs many proposals to reform and renew this fundamental democratic institution. This reading also speaks to our collective desire for parliaments to be places for discursive engagement among our elected representatives. It is, after all, figures like Franklin Delano Roosevelt, Winston Churchill, and Pierre Elliott Trudeau – the brightest minds and the best orators – who fill our political imagination and play the role of archetypal legislator in our political mythology. Watching debate in the BC Legislature, we found that there was certainly no shortage of ‘talking’. But while facts, messages and information abounded, they type of substantive dialogue and conversation that ideally lead to elucidation and edification were often at a premium. In Question Period and debate alike, ministers and members often spoke past each other in a battle of messages. The tendency to speak in sound bites and avoid rather than rebut opponents’ arguments diminished the potential for dialogue inside the chamber. Legislators, however, often invoked a different audience and implicitly addressed their remarks to this group outside of the chamber. This group is the public. Indeed, it is the observers of legislative debates who are frequently invoked by legislators, and who are the intended recipients of the messages delivered during events like Question Period. The clip format used for stories in the evening news creates both an imperative and a receptacle for the thirty second sound bites legislators use to communicate with the public, and with voters. If one has only a limited amount of time in which to communicate with this important group, it is understandable that one would want to be seen delivering a positive message rather than attempting to engage with an opponent in a discussion that could easily be construed as ‘bad news’. In many ways the public is now the intended recipient of legislators’ statements in the House, and it is the public that has become an increasingly important party in a ‘conversation’ that had previously been largely confined within the walls of legislatures. While the effects of the media on politics have been widely studied, it is the shifting locus of conversation from within legislatures and out to the public that we wish to discuss here. It is our belief that developments in communications technology

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)0.012
metaresearch head score (Gemma)0.030
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: Commentary · Consensus signal: none
Teacher disagreement score0.979
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.030
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0110.035
Scholarly communication0.0090.007
Open science0.0020.003
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0120.002

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 head0.066
GPT teacher head0.301
Teacher spread0.235 · 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
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

Citations0
Published2008
Admission routes1
Has abstractyes

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