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Record W2989779875 · doi:10.7939/r3-kqyt-b515

National Myth in Canada: Reproducing and Resisting Settler Colonialism at Memorial Sites

2019· article· en· W2989779875 on OpenAlexaboutno aff
Jason Chalmers

Bibliographic record

VenueUniversity of Alberta Library · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicVietnamese History and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsColonialismMythologyPolitical scienceHistoryLawClassics

Abstract

fetched live from OpenAlex

This dissertation examines myth and memory in settler colonial contexts. In particular, it explores the way Canadians engage with national mythology at sites of genocide commemoration. It focuses on three national sites that together constitute a memorial network: the Canadian Museum for Human Rights (CMHR), which opened in Winnipeg in 2014; the Truth and Reconciliation Commission (TRC), which released its final report in 2015; and the National Holocaust Monument (NHM), which was unveiled in Ottawa in 2017. These sites are ideal case studies because each addresses the history and memory of the Holocaust or Residential Schools. The history and memory of genocide, and especially Indigenous genocide, is an integral part of settler colonialism and settler mythology. In this dissertation, I ask how sites of genocide memory reproduce – or resist – settler colonialism in Canada. I consider how memory functions as an aspect of settler colonialism and, especially, how Canadians use commemoration to reinscribe settler mythologies, identities, and relationships. Furthermore, I address how these memories can become sites of resistance that destabilise settler colonialism. My analysis is guided by the framework of difficult knowledge. The theory of difficult knowledge posits that learning occurs when marginalised narratives (difficult knowledge) disrupt dominant ones (lovely knowledge). This study considers how the CMHR, TRC, and NHM frame histories of genocide as difficult and/or lovely knowledge. I demonstrate that, while the NHM reproduces lovely knowledge, the TRC and CMHR both generate potentially difficult knowledge, albeit in limited ways. However, they use different techniques to do so: the TRC promotes a subversive counter-narrative whereas the CMHR encourages visitors to engage in the interpretation of national history. I contend that they are likely to produce difficult knowledge about Canadian history and myth when they engage with Indigenous peoples and perspectives. Furthermore, I argue that the framework of difficult knowledge can work as a critical – and potentially decolonising – research methodology. This study offers several findings regarding the relationship between settler colonialism and memorial networks. I argue that, while Holocaust memory and the memory of Residential Schools can – and do – inform one another, both memories emerge from and are shaped by settler mythology. In other words, settler colonialism plays a significant role in the production of genocide memory in Canada. Furthermore, I argue that the CMHR, TRC, and NHM are points of rupture that force Canadians to confront the myths and memories that undergird settler society. That is, these sites cultivate identity by enabling people to engage with, re-enact, and institutionalise myth and memory. At the same time, however, memorial sites are places of resistance that can disrupt national myth and destabilise settler colonialism.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.542

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0450.031
Scholarly communication0.0130.004
Open science0.0020.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.190
Teacher spread0.181 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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