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Wisdom of the Elders: Canadian Reconciliatory Experience as an Insight on the Present

2019· article· en· W2987467374 on OpenAlexaffabout
John Soroski

Bibliographic record

VenueLondon Journal of Canadian Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMulticultural Socio-Legal Studies
Canadian institutionsMacEwan University
Fundersnot available
KeywordsIndigenousDignityDeferenceEnthusiasmHarmEnvironmental ethicsValue (mathematics)SociologyPolitical scienceCriminologyLawSocial psychologyPsychology

Abstract

fetched live from OpenAlex

Abstract Canada’s first two large historical encounters of recognition and work-in-progress accommodation of previously marginalized and alienated groups involved French Canada and newcomer Canadians. The third such engagement is now underway in response to the Indigenous peoples of Canada. While this endeavour is long overdue, there is reason for concern that the laudable enthusiasm of many for this project of reconciliation may be authorizing some policies, practices and discourses that conflict with and potentially undermine the values that informed and came out of previous inclusionary encounters. Three areas of concern arise. The first is the embrace of state deference in some instances to unlawful and sometimes violent forms of Aboriginal protest and resistance, undercutting the idea of the rule of law and of the value of the peaceful resolution of disputes. The second is the propensity to under critically over-authorize Indigenous cultural communities as sources of moral valuation, in ways that may undermine individuals’ dignity and well-being, as well as doing harm to the good of intra-cultural inclusiveness. The third is the related tendency to over-valorise Indigenous cultures and claims in ways that suggest symbolically and in practical terms the idea of the existence of morally first-class and morally second-class Canadians.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.633
Threshold uncertainty score0.931

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.063
GPT teacher head0.318
Teacher spread0.255 · 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 teacher head, 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
Published2019
Admission routes2
Has abstractyes

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