Remembering Child Migration: Faith, Nation-Building and the Wounds of Charity
Bibliographic record
Abstract
Between 1850 and 1970, around three hundred thousand children were sent to new homes through child migration programmes run by churches, charities and religious orders in the United States and the United Kingdom. Intended as humanitarian initiatives to save children from social and moral harm and to build them up as national and imperial citizens, these schemes have in many cases since become the focus of public censure, apology and sometimes financial redress. Remembering Child Migration is the first book to examine both the American 'orphan train' programmes and Britain's child migration schemes to its imperial colonies. Setting their work in historical context, it discusses their assumptions, methods and effects on the lives of those they claimed to help. Rather than seeing them as reflecting conventional child-care practice of their time, the book demonstrates that they were subject to criticism for much of the period in which they operated. Noting similarities between the American 'orphan trains' and early British migration schemes to Canada, it also shows how later British child migration schemes to Australia constituted a reversal of what had been understood to be good practice in the late Victorian period. At its heart, the book considers how welfare interventions motivated by humanitarian piety came to have such harmful effects in the lives of many child migrants. By examining how strong moral motivations can deflect critical reflection, legitimise power and build unwarranted bonds of trust, it explores the promise and risks of humanitarian sentiment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.023 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| 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".