Bibliographic record
Abstract
This chapter explores the story of a ‘home child’ (pseudonym Katherine) who was sent to Canada at the age of nine to be indentured on a farm at the turn of the 20th century. Her mother, widowed and impoverished, could not afford to keep her. She was promised by UK evangelists, as were many poor families of the time, that in return for being indentured on a farm in Quebec, Katherine would receive an education. This narrative is the result of a series of interviews conducted with one of her daughters (pseudonym Margaret) and is portrayed in a letter to her grandchild. The chapter posits how the social context of industrialization in the United Kingdom at the time, and the need for rural workers in Canada, provided a ‘perfect context’ for the shipping of approximately 80,000 children to Canada over a period of 60 years. It details in the methodology, the life-long impact that this displacement had on Katherine as she ‘ strove to belong,’ ‘suppressed the past,’ and was always ‘compensating’ for her feeling of displacement. It concludes with a discussion of the implications of this story.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.019 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".