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Record W3118931846 · doi:10.22215/etd/2014-10506

The Hybrid Monumental Symbols of Canada's Warrior Nation Moment

2014· dissertation· en· W3118931846 on OpenAlexaboutno aff
Ian Mortimer

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicMilitary History and Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsMilitarismRebrandingIdentity (music)Period (music)Government (linguistics)AdvertisingPolitical scienceMedia studiesLawEngineeringHistorySociologyArtPoliticsAestheticsBusinessMarketing

Abstract

fetched live from OpenAlex

The Harper government led a project of rebranding of Canadian identity in the period following the 2011 election. This study focuses on three militaristic symbols from this period as important cultural texts unto themselves, best described as Hybrid Monumental in form. They communicate a monumental vision of Canada, defined by war and sacrifice for the nation. However, they are all hybridized through the layering of established symbols of Canadian identity, tempering their monumental messaging. These symbols are the product of a mutual commitment amongst the Harper Government and key stakeholders to market themselves as iconic brands. This reality has created an environment where not even Canadian soldiers’ deaths are immune from being co-opted and collapsed into brand marks, used to target certain customers and hopefully secure their votes, while remaining ambiguous enough to allow the brand’s image to shift and move on when market conditions, popular opinion on war) changes.

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)0.001
metaresearch head score (Gemma)0.002
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: Other · Consensus signal: Other
Teacher disagreement score0.061
Threshold uncertainty score0.401

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0260.024
Scholarly communication0.0110.002
Open science0.0010.003
Research integrity0.0010.003
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 head0.009
GPT teacher head0.248
Teacher spread0.240 · 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
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
Published2014
Admission routes1
Has abstractyes

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