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Record W1600360642 · doi:10.3138/jcs.46.1.193

Broadening the Political Constituency of Tax Reform: The Visual Rhetoric of <i>Canadian Taxation</i>, 1979-81

2012· article· en· W1600360642 on OpenAlexvenueaboutno aff
David Tough

Bibliographic record

VenueJournal of Canadian Studies · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicLiterature, Musicology, and Cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsRhetoricHumanitiesPolitical sciencePoliticsDemocracyTax reformSociologyLawArtPhilosophy

Abstract

fetched live from OpenAlex

Published between 1979 and 1981, Canadian Taxation reflected an attempt by Neil Brooks and other tax scholars to democratize debates on taxation in Canada. Contributors drew on a critique of taxation that had emerged through the Royal Commission on Taxation (1962-67) and the controversial amendments to the Income Tax Act that followed. In its earliest issues, it used language, images, and design to popularize a left-wing understanding of Canada’s tax system as benefitting the rich. Over its three-year publication run, the magazine reverted to a more austere visual style and professional tone, effectively abandoning its early democratizing ambitions. This essay studies the visual rhetoric of Canadian Taxation as a historically important attempt to make tax debates resonate outside specialist circles, and as a model for a more generous scholarship that would use rhetoric to present taxation not as a technical field of expertise but as a key activity of modern democratic citizenship.

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)0.002
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.134
Threshold uncertainty score0.972

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0300.028
Scholarly communication0.0140.003
Open science0.0010.002
Research integrity0.0020.004
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 head0.049
GPT teacher head0.325
Teacher spread0.276 · 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

Citations0
Published2012
Admission routes2
Has abstractyes

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