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Record W4413377392 · doi:10.33137/ijournal.v10i3.45892

Sharing Histories of Immigration

2025· article· en· W4413377392 on OpenAlexvenueaboutno aff
Jacob Fralic, Vasiana Moraru

Bibliographic record

VenueThe iJournal Student Journal of the Faculty of Information · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationPolitical scienceHistoryArchaeology

Abstract

fetched live from OpenAlex

Ontario and the Greater Toronto Area have become the home for many different immigrant communities, and the Mennonite Archives of Ontario stands out amongst the many museums and cultural centers catering to these communities. Their most recent exhibit, What They Carried: The Archives of Russlaender Mennonite Immigrants, demonstrates the potential of the Mennonite Archives’ collection for creating and sharing narratives of the Mennonite community in Canada. By researching the history of Mennonite migration, the Archives’ development and actions, and analyzing What They Carried, we have found that the stories and experiences shared by the Mennonite Archives of Ontario transcends typical collection and preservation practices to become a space that actively engages with the Mennonite community in Ontario.

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)0.009
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.732
Threshold uncertainty score0.540

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0360.022
Scholarly communication0.0110.005
Open science0.0020.013
Research integrity0.0010.002
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 head0.020
GPT teacher head0.323
Teacher spread0.303 · 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
Published2025
Admission routes2
Has abstractyes

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