Caring For/Caring About: Women, Home Care, and Unpaid Caregiving; Nobody's Home: Candid Reflections of a Nursing Home Aide
Bibliographic record
Abstract
Book Review| May 01 2006 Caring For/Caring About: Women, Home Care, and Unpaid Caregiving; Nobody's Home: Candid Reflections of a Nursing Home Aide Caring For/Caring About: Women, Home Care, and Unpaid Caregiving Karen R. Grant, Carol Amaratunga, Pat Armstrong, Madeline Boscoe, Ann Pederson, and Kay Willson, eds. Aurora, Ontario: Garamond, 2004 208 pp., $24.95 (Canadian) (paper) Eileen Boris Eileen Boris Search for other works by this author on: This Site Google Labor (2006) 3 (2): 138–140. https://doi.org/10.1215/15476715-2005-018 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn Email Tools Icon Tools Permissions Cite Icon Cite Search Site Citation Eileen Boris; Caring For/Caring About: Women, Home Care, and Unpaid Caregiving; Nobody's Home: Candid Reflections of a Nursing Home Aide. Labor 1 May 2006; 3 (2): 138–140. doi: https://doi.org/10.1215/15476715-2005-018 Download citation file: Zotero Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search Books & JournalsAll JournalsLabor Search Advanced Search The text of this article is only available as a PDF. Labor and Working-Class History Association2006 Article PDF first page preview Close Modal You do not currently have access to this content.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".