A historical survey concerning marketing middlemen as producers of value
Bibliographic record
Abstract
Purpose The purpose of this paper is to trace from ancient Greek scholars to the mid‐1950s the sentiments of two schools of economic thought on the role of marketing middlemen or intermediaries. One school disclaims any addition of value through middlemen's activities; the second maintains that marketing adds value. Design/methodology/approach This paper was originally a chapter in the author's doctoral dissertation titled “Value added as a measure of economic contribution by marketing institutions” at Ohio State University. It is reprinted here to explore and add insight to other work by and about the author in this issue of the journal. A brief historical analysis of writings by ancient Greek scholars, mercantilists, physiocrats, classicists, neoclassicists, and twentieth century dissenters, is presented. Findings Marketers add value and, in so doing, are productive. However, earlier scholars did not distinguish between measures of value added and measures of productivity and efficiency. Originality/value While other marketing historians have covered much of this literature since the time of its original writing, it was in 1957 among the earliest such work by marketing scholars. As mentioned above, this paper explores and adds insight to other work by and about the author in this issue of the journal.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".