Bibliographic record
Abstract
Rebecca White’s article examines the origins of a new state-funded welfare system in Maine through the prism of the 1917 “Act to Provide for Mothers with Dependent Children,” also known as mothers’ aid or mothers’ allowance legislation. This law established a centralized Mothers’ Allowance Board in Augusta to oversee applications and administer state funding to eligible Maine families. This represented a shift from traditional town-based poor services to a state-funded system of aid for those considered to be worthy. This article details the sparse landscape of public and private charity available to families in the nineteenth and early twentieth centuries in Maine, in particular the town-based pauper-relief and poor[1]farm systems common across the state. It then presents the ideological and practical processes that led to Maine’s adoption of this new centralized approach to public welfare. Rebecca White earned her PhD in Canadian-American History from the University of Maine in 2015 and her MA in European History from the University of Pittsburgh in 2002. Her research agenda focuses broadly on women, gender, and the impacts of the modernizing state in United States and Canada. Her current project looks at the gendered and class-based ideologies and practices of anti-tuberculosis efforts in the Province of New Brunswick, with a particular focus on the interplay of public welfare and public-health officials in casework and case-finding efforts. White’s dissertation examined the social history of mothers’ allowances in Maine and New Brunswick. The study explained the power structures and ideological basis of these state welfare programs and highlighted ways that women, families, and com[1]munities worked within these rigid systems to assert some level of independence. These same themes of gender, authority, and power infuse her teaching in the Women, Gender, and Sexualities Studies and History Department at the University of Maine.
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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 | 0.004 |
| 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 | 0.010 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".