Managing business political activities in the USA: bridging between theory and practice — another look
Bibliographic record
Abstract
Abstract This paper provides a review and reflection of Gerry Keim's fine paper on managing US business political activities (BPA). It begins by setting the larger context in which BPA is both practised and studied. It critiques the concept of market‐based competition and extends it by suggesting that non‐market competition can take on a myriad of forms dependent on strategy and structural considerations, among other things. It also provides some sober reminders about the nature of difficulties encountered between academics and practitioners in bridging the gaps of understanding between these constituencies. It also looks at the nature of ‘buyers’ and ‘sellers’ in the public policy marketplace and expands upon the nature of the products being exchanged. Lastly, the paper reviews the nature of strategy and competitive advantage in the non‐market environment and recommends a practitioner focus on innovation and the acquiring of the resources needed for institutionalizing it in their public affairs and BPA efforts for achieving non‐market success. Copyright © 2001 Henry Stewart Publications
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.015 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".