Resenha bibliográfica do livro Crescimento Econômico e Crise na Argentina de 1870 a 1930: A Belle Époque de Maria Heloisa Lenz
Bibliographic record
Abstract
A tese de Maria Heloisa Lenz, transformada em livro, e um bem sucedido esforco de reconstrucao da historia economica argentina nos sessenta anos que antecederam a crise da decada de 1930. Com o e consensual entre os estudiosos, a economia argentina apresentou neste periodo de analise, notadamente nos anos finais do seculo XIX e iniciais do seculo XX, um processo de crescimento economico impar na sua historia, mesmo quando comparado com as nacoes atrasadas, ou seja, com caracteristicas de um desenvolvimento economico tardio, como a Australia, o Canada, a Nova Zelândia e os Estados Unidos.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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; both teacher heads agree on what is shown here.
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".