Bibliographic record
Abstract
In the 1660s and 1670s, the French Crown, influenced by the hardening of racial boundaries, grew increasingly concerned about the political, social, economic, and religious implications of mixed-race relationships in New France. In cooperation with the Minister of Finance and the Secretary of the Navy Jean-Baptiste Colbert, King Louis XIV of France created a state-sponsored child-trafficking program known as the filles du roi , or king’s daughters. The French Crown sent over 760 filles du roi to its territories in North America, primarily those in Canada, to serve as suitable wives for the colony’s bachelors. Far from the king’s actual daughters, filles du roi were oftentimes orphans and wards of the state, the majority of whom were in their late teens. Focusing on some of the youngest filles du roi and using census data, ship logs, birth records, marriage contracts, and death records, this chapter argues that the French empire sought to build its imperial territory, power, and glory on the back and in the wombs of children in the late seventeenth century. This chapter also explores how age—especially youth—could be manipulated to serve the various needs and desires of institutions of power.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.039 | 0.009 |
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".