What do historians really think about biography?
Bibliographic record
Abstract
This article explores the ways in which historians have thought about biography as a genre of writing about the past and how these attitudes have changed over the last fifty years or so, from skepticism and even hostility to increasing acceptance and even advocacy. It also examines some of the ways in which biography itself has evolved and the contribution of historians to this evolution, before concluding with an example from the author’s forthcoming biography of the 19th-century Spanish military and political figure Baldomero Espartero (1793-1879).***O que os historiadores realmente pensam sobre a biografia?***Este artigo examinava as varias caminhas que os historiadores pensava sobre o válor do gênero da biografia nas considerações do nosso passado, e a mudança nas manieras de ver biografia entre nos ultimos cinquentos anos: atitudes alterava de cetecismo e oposição ao aceitação, confiança, e promoçåo da biografia a un gênero respeitável da História. Tambem, o artigo considerava o evolução da biografia e o contribução dos Historiadores ao aquele evolução. Finalemente, o artigo vai concluir com un exemplo da biografia – que vai publicar sobre Baldomero Espartero (1793-1879) – escrevendo do mesmo autor deste artigo.
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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 | 0.009 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.009 | 0.033 |
| Scholarly communication | 0.021 | 0.026 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".