Bibliographic record
Abstract
This is the first of a two‐part paper, which reviews the evolution of the supply management function from the 18th century to 1940. A second paper will examine the continued evolution of supply management from 1940 until the present. The 1830–1940 period in North America was one of tremendous development for purchasing. It started with occasional reference in management texts and, particularly after 1900, saw the evolution of a host of ideas representing the foundation of today's perspective on supply management. At no time did purchasing practitioners and academics see the function as a narrow buying activity. Clearly, our predecessors were well aware of the benefits of integration and would have been comfortable with today's supply chain management precepts. They also recognized value, cost and price analysis, value analysis, purchasing research, talent management, outsourcing the supply function, supplier relationships, strategy and the need for performance measurement. They strived to contribute effectively to organizational goals and strategies, well aware of the potential impact of their actions on organizational success. An understanding of supply's evolution may not only assist today's supply management practitioners and academics in placing current practices and theories in context but also in charting our future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".