Curating the American Past: A Memoir of a Quarter Century at the Smithsonian National Museum of American History
Bibliographic record
Abstract
In the introduction to Curating the American Past, Pete Daniel tells us what to expect: “Attacking is far more exciting than defending” (3). The remainder of the book makes good on that epigram as Daniel chronicles his career as a curator at the Smithsonian Institution's National Museum of American History (1982–2009). He acknowledges that he approached the work with “a naïve belief that [the Smithsonian] soared above political skirmishes and lived up to its sterling reputation as a temple of learning” (7). Daniel describes the first twenty years as “frantic with collecting, exhibits, writing books, and exciting projects,” but his frustration grew as “visionless leadership” eviscerated the curatorial staff (7–8).Daniel makes clear that the memoir grew out of frustration that existed earlier in his curatorial career but that escalated over time. This warning should prepare readers for blunt and often critical assessments. He shares names and pulls no punches. He does not try to reason through decisions that he believed threatened the museum's integrity. Instead, Daniel lays out the facts as he perceived them and leaves it to others who care about intellectual rigor, public engagement, exploration of crucial history, and museum ethics to investigate further.Real nuggets abound in Curating the American Past. Those who know Daniel's publications will become acquainted with his public history side, such as the relationship between his work on the exhibition Science in American Life, which opened in April 1994, and his book Toxic Drift (2007). Those who know Daniel through his work with Smithsonian Fellows will learn more about how selected fellows’ study of Southern rural life and history enhanced collections and scholarship alike. All readers will learn more about the heavy lift that curation involves, especially when the subject—agriculture—becomes subsumed under numerous other themes more appealing to donors. This probably accounted for administrative decisions that undermined Daniel's goals to curate an exhibit in his area of expertise (rural Southern life). Frustrated but undeterred, he documented that past and wrote about it. His award-winning articles and books stand as permanent evidence of his thoughtful and detailed framing of a South that he lived, researched, and preserved for future reference.Surveys indicate that public trust in museums remains high, and that the public expects museums to address crucial history, the type of history that Daniel spent his career researching, collecting, and writing about, and encouraging numerous Smithsonian fellows to pursue the same. While no exhibit stands as a testimony to Daniel's Smithsonian career, Curating the American Past makes clear that his tenacity in defending historical work stands as a lasting and befitting legacy of his influence on agricultural history.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.013 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".