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Record W2006795892 · doi:10.1353/utq.2012.0030

Painting for Profit: The Economic Lives of Seventeenth-Century Italian Painters (review)

2012· article· en· W2006795892 on OpenAlexvenueno aff
Alexander Nagel

Bibliographic record

VenueUniversity of Toronto Quarterly · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicArt History and Market Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPaintingPremiseArt historyArtHistoryPhilosophy

Abstract

fetched live from OpenAlex

Reviewed by: Painting for Profit: The Economic Lives of Seventeenth-Century Italian Painters Alexander Nagel (bio) Richard E. Spear and Philip Sohm. Painting for Profit: The Economic Lives of Seventeenth-Century Italian Painters. Yale University Press. 400. $85.00 The real lives of seventeenth-century Italian artists were, with few exceptions, nasty and brutish. As Raffaella Morselli, one of the authors in this collection, observes, ‘Painters became and remained poor in a variety of ways.’ The premise of this book is that we are not really seeing the art of this period until we come to grips with the tough economic realities that artists faced. Don’t take the empty stretches of canvas in the later paintings of Guercino simply as expressions of a minimalist aesthetic. Fed up with patrons who did not pay the correct amount, he delivered paintings with fewer figures than they bargained for. No one would deny that more information of this sort is helpful and necessary to know. It is equally true that we need lots of it for the information to rise above the level of the anecdotal. This book is presented as a survey of findings from various regions of Italy, with essays on Rome (Richard Spear), Naples (Christopher R. Marshall), Bologna (Raffaella Morselli), Florence (Elena Fumagalli), and Venice (Philip Sohm). Two efforts at a round-up by the economic historians Renata Ago and Richard A. Goldthwaite make it clear how difficult it is to see clear patterns in the data. Painting had undeniably achieved a new cultural standing by 1600, and yet (possibly for that very reason) the protocols for monetizing that value were unclear. Some painters and buyers adhered to the old guidelines whereby size, materials, and the number of figures determined price; others embraced more modern, intangible criteria. With [End Page 772] few exceptions, such as the superstar Guido Reni, the lack of systematically applied criteria was to the disadvantage of the artists. There are many tables in this book, and they are extremely useful, often enough because they make it clear just how hard it is to draw patterns from the data. Global conclusions are occasionally drawn out of them, for example that pricing in Venice was primarily by size of the picture rather than the number of figures, but such global conclusions are rare. And yet the accumulation of these numbers, disparate as they are, does induce a different view of things. One cannot come away from this book and still see swift and open brushwork, a defining feature of a good deal of painting after 1600, as a purely stylistic matter. There is no getting around the fact that it was a real solution to the pressures of time and money that most artists faced – a solution, of course, legitimized by a new aesthetic that allowed and cultivated the taste for it. To see the stylistic fact in the context of the hard economic reality is to view the paintings more subtly, not less. Even as the insufficiency of the available data is lamented, the unchallenged premise throughout the book is that empirical information about pricing and earnings can tell us something fundamental about the kinds of paintings that were produced and the way they look. Well, almost unchallenged: Richard Goldthwaite is the only author in the collection to confront head-on the difficulty of drawing a useful link between economics and artworks. He points out, first off, that expenditures on paintings constitute an infinitesimal portion of the overall economy, and yet leaving that aside, taken on its own, this sector reveals a basic incoherence. ‘The authors of this volume, whose charge was to say what they could about the subject, have produced arrays of prices that almost defy analysis.’ In other words, there was a basically unsystematic relation between art and money, beyond our incidental difficulty in reconstructing the relationship on the available evidence. As Goldthwaite puts it, ‘[T]he cultural value of paintings was not expressed in the market.’ Such a contention, offered at the end of the book, opens a perspective onto a different line of inquiry. With no pricing system in place, immediate precedents and relevant comparisons counted for a great deal, suggesting...

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.600
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.013
GPT teacher head0.197
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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Same venueUniversity of Toronto QuarterlySame topicArt History and Market AnalysisFrench-language works237,207