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Record W4398178033 · doi:10.4324/9781003391524-5

New futures for famine pasts?

2024· book-chapter· en· W4398178033 on OpenAlexaboutno aff
Marguérite Corporaal, Jason King

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsnot available
Fundersnot available
KeywordsFamineFutures contractHistoryArchaeologyEconomicsFinancial economics

Abstract

fetched live from OpenAlex

The strong presence of Ireland&s;s Great Famine and its Canadian diaspora has always had a prominent place in public memory cultures in Ontario and Quebec. By contrast, this catastrophe and its aftermath—the establishment of quarantine stations to care for diseased Irish emigrants who arrived on Canadian soil—have played a relatively minor role in past and present secondary education in both provinces. This chapter aims to clarify this phenomenon, not only through interviews with present-day teachers from the greater Toronto and Montreal area but also through an in-depth analysis of recurrent narrative templates in early and very recent history textbooks. It argues that the Famine Irish immigrant story resonates in particular for Quebec&s;s English-speaking minority teachers and students who often feel excluded from the province&s;s history curriculum.

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)0.001
metaresearch head score (Gemma)0.001
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: Other
Teacher disagreement score0.400
Threshold uncertainty score0.795

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.011
Scholarly communication0.0060.005
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0180.002

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 head0.037
GPT teacher head0.307
Teacher spread0.271 · 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
Published2024
Admission routes1
Has abstractyes

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