Bibliographic record
Abstract
Our collaboration began when we accidentally bumped into each other, intellectually speaking.In March 2011, we had been assigned to the same panel by another colleague at a scholarly conference in Montreal, Quebec.At the time, we knew one another only casually.First, Jesse Spohnholz presented about a series of pastors and other Reformed churchmen who were refugees in Wesel (the topic of his first book).Next, Mirjam van Veen presented on a series of opponents of orthodox Calvinists who rejected dogmatic forms of religion (the topic of her first book).As it turned out, our papers were on the exact same people!Many of the Dutch Republic's most notorious so-called libertines had spent time in refugee communities in the Holy Roman Empire in the 1560s and 70s.Did these examples demand that we rethink the commonplace treatment of exile as a contributor to doctrinaire and steadfast forms of orthodox Calvinism?Why had scholarsincluding ourselves-failed to see these counterexamples before?Through conversations that followed, we began asking all sorts of new questions and wondering what would happen if we started looking at a fuller spectrum of refugees' experiences and impacts.Over time, we developed a collaborative research project.Our goal was to understand the diversity of exiles' experiences and to see if we could make sense of the resulting impacts of those experiences.We did not set out to prove that exiles were either more or less tolerant than anyone else, or that exile had any particular effect on migrants, their hosts, or their future homes.Instead, we were driven by an open curiosity.In 2014, the Dutch Research Council (Nederlandse Organisatie voor Wetenschappelijk Onderzoek) awarded us a grant to investigate our questions and develop answers to them.We wish to thank a number of colleagues who provided particular help as this project developed.They include (alphabetically)
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.944 | 0.898 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".