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Record W2939592347 · doi:10.1177/0896920519844568

Monumental Panic: Reconciliation, Moral Regulation, and the Polarizing Politics of the Past

2019· article· en· W2939592347 on OpenAlexaffabout
Sean P. Hier

Bibliographic record

VenueCritical Sociology · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Deviance, and Social Control
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsStatuePoliticsPrime ministerMoral panicLawPolitical scienceSociologyEconomic historyHistoryPolitical economyReligious studiesArt historyPhilosophy

Abstract

fetched live from OpenAlex

In 2018, the City of Victoria, British Columbia, Canada removed a statue of Sir John A. Macdonald from the grounds of City Hall. As Canada’s first prime minister, Macdonald is both revered for the role he played in Confederation and vilified for enacting and promoting racist if not culturally genocidal policy initiatives aimed at destroying Indigenous cultures in the last part of the 19th century. Set in the context of truth and reconciliation politics playing out across the country, this article explains the removal of the monument and the social reactions it provoked, using the sociologies of moral panic and moral regulation. By focusing on one city council’s efforts to interpret and act on the moral imperatives associated with political reconciliation in post-colonial Canada, insights are provided into some of the practical challenges and potential contradictions that municipal governments can encounter when they adopt idiosyncratic strategies to atone for historical injustices in non-transitional democratic nations.

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)0.006
metaresearch head score (Gemma)0.006
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: Empirical
Teacher disagreement score0.534
Threshold uncertainty score0.938

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0360.148
Scholarly communication0.0190.004
Open science0.0020.007
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.313
Teacher spread0.290 · 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 routes2
Has abstractyes

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