Chapter 15 Reading Migration Literature through a Mobility Studies Lens
Bibliographic record
Abstract
The Routledge Companion to Migration Literature offers a comprehensive survey of an increasingly important field. It demonstrates the influence of the “age of migration” on literature and showcases the role of literature in shaping socio-political debates and creating knowledge about the migratory trajectories, lives, and experiences that have shaped the post-1989 world. The contributors examine a broad range of literary texts and critical approaches that cover the spectrum between voluntary and forced migration. In doing so, they reflect the shift in recent years from the author-centric study of migrant writing to a more inclusive conception of migration literature. The book contains sections on key terms and critical approaches in the field; important genres of migration literature; a range of forms and trajectories of migration, with a particular focus on the global South; and on migration literature’s relevance in social contexts outside the academy. Its range of scholarly voices on literature from different geographical contexts and in different languages is central to its call for and contribution to a pluriversal turn in literary migration studies in future scholarship. This Companion will be of particular interest to scholars working on contemporary migration literature, and it also offers an introduction to new students and scholars from other fields. Chapter 15 of this book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons [Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND)] 4.0 license.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".