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Record W2741980663

Challenging Canadian Identity

2017· article· en· W2741980663 on OpenAlexaboutno aff
Shannon Rogers, Erin Clancy, Leah Maxwell, Joshua Lewis Thomas

Bibliographic record

VenueQSpace (Queen's University Library) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsIdentity (music)Computer sciencePhilosophyAesthetics
DOInot available

Abstract

fetched live from OpenAlex

We chose the curriculum unit of 1982-Present in the Grade 10 Introduction to Canadian History course because it is often one that we have seen neglected in our experience as students and Teacher Candidates. Since the course spans a long period of time, many teachers do not leave sufficient time or run out of time for this area of the course, meaning that this unit is often absent or rushed. We chose to create resources and lesson plans for this unit so that we could bring attention to many events and issues that would help students understand Canadian History to the present. The central theme of our unit is “Challenging Canadian Identity” because many of the topics explored in the period of 1982 - Present have repercussions that challenge the stereotype or “typical” Canadian identity. We feel that exploring these topics will allow students to develop the skills necessary to look at themselves as Canadians through multiple lenses, therefore also developing their own multi-faceted identities as responsible Canadian citizens. We want the students to understand that there is not one cohesive “Canadian identity” and we want them to have the skills to be able to challenge the generally accepted norms.

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)0.005
metaresearch head score (Gemma)0.011
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 score0.194
Threshold uncertainty score0.935

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0950.028
Scholarly communication0.0270.008
Open science0.0020.012
Research integrity0.0080.012
Insufficient payload (model declined to judge)0.0310.002

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 head0.010
GPT teacher head0.196
Teacher spread0.186 · 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
Published2017
Admission routes1
Has abstractno

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