Quantifying Relevance in Art Exhibition Systems at the Turn of the Twentieth Century: A Case Study of a Cultural Network Approach
Bibliographic record
Abstract
This paper presents a digital humanities framework for the study of the art exhibition phenomena in Europe in the late nineteenth and first half of the twentieth centuries, which deploys a mixed-methods approach based upon the concept of relevance. This matter is examined from the perspective of art history, previous contributions are discussed, and the rationale for the proposed framework is specified. After modelling the exhibition phenomenon as a cultural network, the calculation of a relevance index is developed and the defined attributes, values, and weights used in this method are thoroughly described. Finally, this conceptualization is tested on a case study of a dataset that comprises 2,845 solo exhibitions held in Barcelona (Spain) and surrounding municipalities between 1890 and 1938, setting grounds for improvement through future iterative work. Cet article présente un cadre en humanités numériques pour l'étude du phénomène des expositions d'art en Europe à la fin du XIXe siècle et pendant la première moitié du XXe siècle, qui utilise une approche mixte fondée sur le concept de pertinence. Cette question est examinée du point de vue de l'histoire de l'art, les contributions précédentes sont discutées, et la justification du cadre proposé est précisée. Après avoir modélisé le phénomène des expositions comme un réseau culturel, le calcul d'un indice de pertinence est développé, et les attributs, valeurs et poids définis dans cette méthode sont décrits en détail. Enfin, cette conceptualisation est testée sur une étude de cas d'un ensemble de données comprenant 2 845 expositions individuelles organisées à Barcelone (Espagne) et dans les municipalités environnantes entre 1890 et 1938, jetant les bases d'améliorations grâce à des travaux itératifs futurs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".