Wal-Mart innovation and productivity: a viewpoint
Bibliographic record
Abstract
Abstract Technology effects, business process development, and productivity growth are considered in the context of a single company: Wal-Mart. The starting point is the 2001 McKinsey Global Institute report, which finds that over 1995–2000, a quarter of U.S. productivity growth is attributable to the retail industry, and almost a sixth of that is attributable to Wal-Mart. Wal-Mart is interesting as well because of its rapid growth in Canada. This is now Canada's largest private sector employer. We also consider other evidence relevant to public policy formation concerning Wal-Mart and conclude with a discussion of options for partially filling important data gaps. On considère les effets de la technologie, le développement des processus d’affaires, et la croissance de la productivité dans le contexte d’une seule compagnie : Wal-Mart. Le point de départ est le rapport de 2001 du McKinsey Global Institute qui révélait que, pour la période 1995-2000, le quart de la croissance de la productivité aux Etats-Unis était attribuable au commerce de détail, et un sixième à Wal-Mart. Le cas Wal-Mart est aussi intéressant à cause de sa croissance rapide au Canada. C’est maintenant le plus grand employeur privé au Canada. On considère certains résultats pertinents pour la formation de la politique publique en ce qui concerne Wal-Mart, et on conclut par une discussion des options ouvertes pour résoudre des problèmes de trous importants dans les données.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".