Letters across borders : the epistolary practices of international migrants
Bibliographic record
Abstract
Introduction B.S.Elliott, David A.Gerber & S.M.Sinke PART ONE: LIMITS AND OPPORTUNITIES How Representative are Emigrant Letters? An Exploration of the German Case W.Helbich & W.D.Kamphoefner The Limits of the Australian Emigrant Letter E.Richards Marriage through the Mail: North American Correspondence Marriage from Early Print To the Web S.M.Sinke PART TWO: WRITING CONVENTIONS AND PRACTICES Irish Emigration and the Art of Letter-Writing D.Fitzpatrick The Importance of Correspondence in Lithuanian Immigrant Life D.Markelis Epistolary Communication between Migrant Workers and Their Families M.A.Vargas PART THREE: SILENCES AND CENSORSHIP Epistolary Masquerades: Acts of Deceiving and Withholding in Immigrant Letters D.A.Gerber Reading and Writing across the Borders of Dictatorship: Self-censorship and Emigrant Experience in Nazi and Stalinist Europe A.Goldberg PART FOUR: EDITORIAL INTERVENTIONS Polish-American Letters to the Editors of Ameryka-Echo, 1922-1969 A.D.Jaroszynska-Kirchmann Immigrant Letters in the Periodical Press in Late Nineteenth-Century Wales W.Jones PART FIVE: NEGOTIATIONS OF IDENTITY Negotiating Space, Time, and Identity: The Hutton-Pellett Letters and a British Child's Wartime Evacuation to Canada H.Brown The Ukrainian Government-in-Exile's Postal Network and the Construction of National Identity K.Lemiski PART SIX: LETTERS AND THE STATE Immigrant Petition Letters in Early Modern Saxony A.Schunka Emigrant Correspondence with Russian Consulates in Montreal, Vancouver, and Halifax, 1899-1922 V.Kukushkin
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".