Bibliographic record
Abstract
Introduction In this part of the book we present eight abbreviated papers that illustrate key aspects of the study of Strategy as Practice. The papers, earlier published in leading management journals, have been chosen because, in different ways, they exemplify well characteristics we believe to be important in papers addressing Strategy as Practice. They provide useful examples of different research methods, of the use of different theoretical lenses, of how research might address and explain the role of actors and activities in organizations, and of how more detailed activities might relate to strategic outcomes or organizational consequences. Given that Strategy as Practice is a newly developing research domain, few of the authors of these papers would identify themselves with that domain, at least when they wrote them. The papers have been selected because all of them have important lessons for scholars who aspire to give future contributions to Strategy as Practice. Each abbreviated paper has the same structure, starting with the original abstract of the paper, followed by a short editors' introduction by the authors of this book, where we present the main reason(s) why the paper has been chosen for inclusion in this book about Strategy as Practice. Then follows the paper summary , using verbatim sections of the paper with linking summaries by ourselves highlighting key aspects of the paper. Finally, at the end of each of the abbreviated papers is an editors' commentary in which we summarize some of the key lessons from each paper as they relate to Strategy as Practice.
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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.114 | 0.030 |
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".