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- Type:
- Article
- Descripción/Resumen:
- As I have previously shown, Alexandre Brongniart established a coherent science of ceramics. By the mid-nineteenth century, Brongniart had popularised the term "la céramique" as a widely-applicable name for the field of pottery and porcelain making, and other related arts. In the Twentieth Century, ceramic manufacturing became increasingly technical. The inclusive field of artisans and industrialists that Brongniart had once envisioned was fracturing. Voices called for the separation of pottery making from experimental, industrial ceramics and the meaning of the term “ceramics” was hotly debated. Numerous etymologies were traced, but, as the predominant language of science transferred from French to English, none of the twentieth-century authors recognized Brongniart’s key role in the invention of the term. Critically, this language debate coincided with and reflected the global politics, nationalism, and warfare of the first half of the Twentieth Century.
- Creador/Autor:
- Carr-Trebelhorn, Julia
- Peticionario:
- Julia Carr-Trebelhorn
- Fecha modificada:
- 03/09/2026
- Fecha modificada:
- 03/09/2026
- Fecha de creacion:
- 2026-03-09
- Licencia:
- Attribution-NonCommercial-NoDerivs 4.0 International
-
- Type:
- Dataset
- Descripción/Resumen:
- CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
- Creador/Autor:
- McCabe, Erin E.
- Peticionario:
- Erin E. McCabe
- Fecha modificada:
- 11/04/2022
- Fecha modificada:
- 11/04/2022
- Fecha de creacion:
- 2022
- Licencia:
- Open Data Commons Attribution License (ODC-By)
-
- Type:
- Dataset
- Descripción/Resumen:
- CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
- Creador/Autor:
- McCabe, Erin E.
- Peticionario:
- Erin E. McCabe
- Fecha modificada:
- 11/03/2022
- Fecha modificada:
- 11/17/2022
- Fecha de creacion:
- 2022
- Licencia:
- Open Data Commons Attribution License (ODC-By)
