Introduction: How We Think of Migration and Mobility
Bibliographic record
Abstract
Introduction: How We Think of Migration and MobilityThe ways in which we, as individuals, understand migration and mobility have deep implications for societies and politics as well as for institutions and everyday practices.This book deals with them in the form of a sociological study.At its core is the duality of migration and mobility, and a possible way to overcome it.My interest in this topic developed while I engaged in fieldwork in the autumn and winter of 2013/14.I left Germany and travelled to Canada to do the first part of my fieldwork, consisting of narrative interviews with people of Polish heritage, which I then continued in Germany in a second pass.During my stay in Toronto, I met Caroline, a thirty-year-old woman, in a café downtown in February 2014. 1 Interviewing her, I learned that she had emigrated from Lodz to Toronto with her parents when she was seven years old.She talked a lot about the circumstances that brought her family to Toronto and about her own experiences in the city.Retrospectively, I see her biographical experience of being a "migrant" of Polish heritage in Canada as corresponding to one typical pattern of (im)mobility I was to outline in this study.While I did not quite know then what it would turn out to be about, something Caroline said struck me because-I can say now as I write this introduction-it captured the problem I was to tackle: "I don't think I would ever leave Canada.I really like living here.Well, maybe for a year.My parents brought me here, and I cannot imagine leaving them here, do you know what I mean?I don't think I can be a second-time immigrant.I've already immigrated once.I went through that."(Caroline, born 1986 in Lodz, my emphasis) 1 I have changed all of my respondents' names in order to guarantee their anonymity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".