Bibliographic record
Abstract
Collective histories and broad social change are informed by the ways in which personal lives unfold. Lives in Transition examines individual experiences within such collective histories during the nineteenth and twentieth centuries. This collection brings together sources from Europe, North America, and Australia in order to advance the field of quantitative longitudinal historical research. The essays examine the lives and movements of various populations over time that were important for Europe and its overseas settlements - including the experience of convicts transported to Australia and Scots who moved freely to New Zealand. The micro-level roots of economic change and social mobility of settler society are analyzed through populations studies of Chicago, Montreal, as well as rural communities in Canada and the United States. Several studies also explore ethnic inequality as experienced by Polish immigrants, French-Canadians, and Aboriginal peoples in Canada. Lives in Transition demonstrates how the analysis of collective experience through both individual-level and large-scale data at different moments in history opens up important avenues for social science and historical research. Contributors include Luiza Antonie (Guelph), Peter Baskerville (Alberta), Kandace Bogaert (McMaster), John Cranfield (Guelph), Gordon Darroch (York), Allegra Fryxell (Cambridge), Ann Herring (McMaster), Kris Inwood (Guelph), Rebecca Kippen (Melbourne), Rebecca Lenihan (Guelph), Susan Hautaniemi Leonard (Michigan), Hamish Maxwell-Stewart (Tasmania), Janet McCalman (Melbourne), Evan Roberts (Minnesota), J. Andrew Ross (Guelph), Sherry Olson (McGill), Ken Sylvester (Michigan), Jane van Koeverden (Waterloo), Aaron Van Tassel (Western).
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.011 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".