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Record W6992950915

National Histories, International Engagements: Can-Am Conference, Montréal: Summer of 2006

2020· article· en· W6992950915 on OpenAlexaboutno aff

Bibliographic record

VenueÉrudit documents and data repository (Érudit Consortium, University of Montreal) · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Research and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsVariety (cybernetics)KingdomNarrativePerspective (graphical)Work (physics)Canadian studiesNational interest
DOInot available

Abstract

fetched live from OpenAlex

This summer, “National Histories, International Engagements” promises to provide Canadian and U.S. historians with unique opportunities to share their ongoing research and explore the potential of cross-border and cross-cultural studies. The conference, the annual meeting of the Society for Historians of the Early American Republic (SHEAR) will be held, 20 to 23 of July at the University of Montreal. Featuring the work of scholars from Europe and the United Kingdom as well as Canada and the United States, this year’s program reflects the growing interest in the American republic’s northern and southern borderlands and in the Atlantic World between 1776 and 1860. A variety of sessions aim to complicate narratives that are contained (and constrained) by the parameters of the nation-state. Many either place U.S. and Canadian histories in transnational perspective or use separate, nation-based studies to compare the two.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.224
Threshold uncertainty score0.504

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0140.003
Scholarly communication0.0090.003
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.1510.015

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 head0.044
GPT teacher head0.244
Teacher spread0.200 · 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 designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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