Reimagining Value Through Artification: A Conceptual and Theoretical Framework for Philanthropy and Marketing
Bibliographic record
Abstract
ABSTRACT Artification, the transformation of non‐artistic objects, practices, or domains into art or art‐like entities, has emerged as a pivotal concept in philanthropy and marketing. This paper develops a conceptual and theoretical framework to examine artification, emphasizing its capacity to add cultural, emotional, and symbolic value across diverse domains. By synthesizing interdisciplinary perspectives, the framework identifies five key components of artification: art infusion, contextual recontextualization, cultural capital accumulation, market and institutional legitimation, and public perception. These elements interact dynamically, illustrating how artification enhances consumer engagement, legitimizes social causes, and elevates brand identity. The framework highlights artification's implications for the third sector, where it strengthens advocacy efforts and fosters emotional resonance, while also critically addressing tensions between authenticity and commodification. This research contributes to understanding artification's transformative potential, offering practical insights for organizations aiming to integrate art into their strategies for differentiation, legitimacy, and societal impact.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.056 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".