Review: <i>Curating the American Past: A Memoir of a Quarter Century at the Smithsonian National Museum of American History</i>, by Pete Daniel
Bibliographic record
Abstract
Book Review| May 01 2023 Review: Curating the American Past: A Memoir of a Quarter Century at the Smithsonian National Museum of American History, by Pete Daniel Curating the American Past: A Memoir of a Quarter Century at the Smithsonian National Museum of American History by Pete Daniel. Fayetteville: University of Arkansas Press, 2022. 260 pp.; 75 images; clothbound, $16.46; eBook, $13.17. Marla R. Miller Marla R. Miller University of Massachusetts Amherst Search for other works by this author on: This Site PubMed Google Scholar The Public Historian (2023) 45 (2): 141–143. https://doi.org/10.1525/tph.2023.45.2.141 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn Email Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Marla R. Miller; Review: Curating the American Past: A Memoir of a Quarter Century at the Smithsonian National Museum of American History, by Pete Daniel. The Public Historian 1 May 2023; 45 (2): 141–143. doi: https://doi.org/10.1525/tph.2023.45.2.141 Download citation file: Ris (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 All ContentThe Public Historian Search Pete Daniel is well known to many public historians as the first practicing museum professional to serve as president of the Organization of American Historians (2008–9; he also had been the first curator to serve in the same role for the Southern Historical Association, in 2005-6). By that time Daniel had spent more than twenty-five years as a curator at the National Museum of American History (NMAH), and so his election signaled for many a real sense of public history’s “arrival.” An award-winning historian of the rural south, Daniel has also authored several monographs on a wide range of subjects rooted in southern, labor, and agricultural history, including his powerful study Dispossession: Discrimination against African American Farmers in the Age of Civil Rights (Chapel Hill: University of North Carolina Press, 2013). Curating the American Past is also a work of labor history—an account of tensions between bosses and workers, contexts... You do not currently have access to this content.
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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.039 | 0.038 |
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".