Bibliographic record
Abstract
“Wall traces the nursing and management roles of nuns and brothers in church-related US health care institutions. This well-documented volume will be a useful addition for collections supporting academic programs in public health, hospital administration, bioethics, and divinity, and for comprehensive collections in the history of medicine. Recommended.” — Choice “ American Catholic Hospitals is fair, balanced, insightful, and intriguing. The story Wall tells—a story about a significant segment of the UShealth care system—is meticulously documented. Readers will find her study to be illuminating, even inspirational.” — Journal of the American Medical Association “In American Catholic Hospitals , Barbra Mann Hall traces the ways Catholic hospitals have accommodated changes both within the church and in society over the last century. Her book is well researched and a fascinating read.” — Health Progress “Wall presents a compelling and well-documented narrative of the dynamic transformation of Catholic hospitals in twentieth-century America. Drawing on records from Catholic congregations throughout the United States, she reveals an admirable perseverance of religious caregivers, demonstrated by their willingness to adapt to socioeconomic forces often inimical to charitable care.” — American Catholic Studies “ American Catholic Hospitals is meticulously researched and well written. Although it is certainly appropriate for both undergraduate and graduate students, general readers also will find it to be an excellent overview of the history of the changes that Catholic health-care institutions have undergone in the twentieth and twenty-first centuries.” — Catholic Historical Review “ American Catholic Hospitals offers a tremendous amount of new material and refreshing perspectives on current health care system challenges in the United States.” —Sioban Nelson, Bloomberg Faculty of Nursing, University of Toronto “Wall provides solid scholarship and engaging insight into the historic and contemporary contributions of American Catholic hospitals and their ability to adapt and serve amid the changing landscapes of church and state, culture wars, and healthcare reforms of the 20th century.” —Carol K. Coburn, author of Spirited Lives: How Nuns Shaped Catholic Culture and American Life, 1836-1920 .
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.292 | 0.094 |
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".