A taxonomy of artists’ postures to grasp the plurality of cultural production practices: Putting an end to the cicada and the ant
Bibliographic record
Abstract
• The rooted art-economy dichotomy does not explain the complexity of artistic activity. • The notion of posture challenges the dichotomy between art and economy. • Artists adopt a multiplicity of postures in today's conditions of cultural production. • A taxonomy of artists’ postures conceptualizes the diversity of artists’ trajectories. • A taxonomy of artists’ postures conceptualizes the complexity of artistic activity. The rooted dichotomy between art and economy tends to simplify our understanding of the conditions under which makers of cultural products operate. The contingencies of the last decades, leading to a greater plurality of artists’ practices, urge us to create new conceptual tools to seize the effective cultural production structures. This paper aims to open this dichotomy - anchored in institutional sociology, creative economy, arts management and cultural entrepreneurship - and to reveal the relational complexity of cultural production. Building on a meta-study of a body of qualitative research published between 2012 and 2022 based on semi-directed interviews, focus groups and case studies about artists’ effective practices in music, performing arts, visual and mediatic arts from underground scenes or marginal communities, we identify 20 postures adopted by artists. We place these postures on two axes reflecting the intensity of economic and artistic logics. This taxonomy explains more accurately today's conditions of cultural production. It allows us to better understand: the multiplicity of artists’ and works’ trajectories, as well as creation networks; the coexistence and co-dependency of postures within the same practice; and the diversity of artists’ practices beyond a disciplinary logic and a linear conception of artistic career.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.008 | 0.027 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".