Eighty Years and More: Looking Back at the Nineteenth Amendment
Bibliographic record
Abstract
Abstract: ‘‘Eighty Years and More – Looking Back at the Nineteenth Amendment’’ is the introduction to a special issue on American Woman Suffrage timed to coincide with the eighty-fifth anniversary of the passage of the Nineteenth Amendment in 1920. The anniversary invites us to raise questions about memory and memorialization, about which stories about suffrage endure (such as Susan B. Anthony’s primacy in the campaign) and which figures and activities have been excluded from myth-making chronicles like the six-volume History of Woman Suffrage. As an overview of the collection, the introduction outlines both the impetuses for and the implications of dismantling traditional narratives of suffrage and refiguring the campaign as a multilayered, multifaceted phenomenon, functioning on many fronts and involving many figures whose efforts have been hidden from history. The special issue as a whole works to challenge old orthodoxies about the suffrage campaign by re-evaluating the contributions of figures like New York author–activist Lillie Devereux Blake and Wyoming justice of the peace Esther Morris and by reconsidering the rhetorical work performed by the creative tactics that characterized the campaign, including oratory, literature, and stereotyping. Reviews of three recent works of scholarship on American suffrage remind us of the persistent interest in interrogating the historiography of suffrage and of the continued need for research that furthers the goals of re-evaluation.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".