Sugar Island Finns : Introducing Historical Network Analysis to Study an American Immigrant Community
Bibliographic record
Abstract
This article will provide a preliminary overview of Finnish migration to Sugar Island, Michigan, which occurred primarily between 1915 and 1940, based on narrative sources and census documents.It will introduce and apply social network analysis (SNA) methods and network visualizations to this community and sets the stage for a future, indepth study of the Finns of Sugar Island.This article is part of a larger project HUMANA-Human Migration and Network Analysis: Developing New Research Methods for the Study of Human Migration and Social Change (https://blogs.helsinki.fi/humananetworks/),funded by the Finnish Kone Foundation.This project will develop new methodologies for studying the human past by using network analysis to better understand social, political, administrative, economic, and geospatial networks.For the purposes of this article, our main sources are the US Census returns from 1920 to 1940, and they will be supported by other archival and secondary sources.The scope of analysis will focus primarily on a few prominent individuals but will also provide information on the social structures of the Finnish community.Ultimately, this case study develops an experimental computer model of the Sugar Island Finnish community and will provide a glimpse into the authors' forthcoming project that aims at building a robust dynamic model of the entire Sugar Island community over the period of 1850-1940.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".