Firm Size and Industry Structure Under Human Capital Intensity: Insights from the Evolution of the Global Advertising Industry
Why this work is in the frame
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Bibliographic record
Abstract
Although existing literature assumes that the human capital intensity of professional services leads to small and flimsy firms, several professional services feature large, long-lived firms. To develop insights about firm size and industry structure in human capital intensive industries, I analyze the structure and evolution of the advertising industry. Drawing on a range of quantitative and qualitative evidence, I develop two hypotheses regarding the industry's structure and consolidation: (1) size differentiation, in which firm size and industry structure are connected to the size distribution of clients' projects, and (2) financial intermediation, in which the industry's consolidation is ascribed to organizational innovations that mitigate transaction costs between external investors and ad agency owners. I then discuss the applicability of these two hypotheses to other professional services. The analysis suggests several new insights about the value of capital, the nature of demand, and the nature of assets in human capital intensive industries.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it