Canadian students’ achievement
Bibliographic record
Abstract
Managing the Partners in Strategic Alliances is a volume in the book series Research in Strategic Alliances that focuses on providing a robust and comprehensive forum for new scholarship in the field of strategic alliances. In particular, the books in the series cover new views of interdisciplinary theoretical frameworks and models, significant practical problems of alliance organization and management, and emerging areas of inquiry. The series also includes comprehensive empirical studies of selected segments of business, economic, industrial, government, and non-profit activities with wide prevalence of strategic alliances. Through the ongoing release of focused topical titles, this book series seeks to disseminate theoretical insights and practical management information that should enable interested professionals to gain a rigorous and comprehensive understanding of the field of strategic alliances. Managing the Partners in Strategic Alliances contains contributions by leading scholars in the field of strategic alliance research. The 14 chapters in this volume deal with significant issues relating to the management of the partners in strategic alliances. These issues run the gamut from deterring deceitful behaviors, partner selection and control, interpartner learning, harmony, negotiation, tensions, and diversities, to partner management and alliance performance. The chapters contain empirical as well as conceptual treatments of the selected topics, and collectively present a wide-ranging review of the noteworthy research perspectives on managing the partners in strategic alliances.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.010 | 0.001 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.276 | 0.069 |
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".