Historical roots and influential publications in the area of innovation in the creative industries: A cited-references analysis using the Reference Publication Year Spectroscopy
Bibliographic record
Abstract
This study explores the historical roots of the relatively new topic of innovation in the creative industries. We are interested in the contributions of researchers that have proven to be important to the topic over the long term. To do so, we used the Reference Publication Year Spectroscopy method. This method is based on the analysis of the frequency with which references are cited in publications in a specific research area, in our case, innovation in the creative industries. The study is based on a corpus of articles rigorously selected through a systematic review method of empirical articles published between 1998 and 2019. The results reveal 4585 cited references (CR) with 9 clearly identifiable peaks, the first of which is caused by the work of Schumpeter (1934) and the last by the book of Miles & Green (2008). Each of the peaks marks a major contribution to the evolution of the understanding of innovation in these industries with one or more publications, the majority of which have an economic basis. In addition, the study reveals that the three most influential publications in this field are the economically oriented books by Florida (2002), Caves (2000), and Miles & Green (2008).
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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 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.082 | 0.115 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".