Chasing After Life: Migrating Childhoods in Valeria Luiselli’s Lost Children Archive
Bibliographic record
Abstract
This essay engages the border-crossing poetics of transnational migration through an engagement with Valeria Luiselli’s fictional depictions of migrant children in her novel Lost Children Archive. Engaging the migrating and intertextual forum of children’s witness and memory in the novel, I follow Luiselli’s moving depiction of child migrants as wholly undocumented and lost people outside the adult world of articulation. I argue that Luiselli’s novel documentation conjures up historical, contemporary, and autobiographical memories of migrant and displaced children comprising the colonial story of modernism. I consider children’s articulations, construction and witness of migration through my readings of the stories of migrating childhood delivered by Luiselli’s fictional depiction. I find, Luiselli’s moving rendition of children’s migration presents new challenges to educational and popular discourses of childhood, migration, and the responsibilities of the adult communities.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.018 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".