Book review: Gino CATTANI, Simone FERRIANI, Lars FREDERIKSEN, and Florian TÄUBE (Eds.) (2011) Project-Based Organizing and Strategic Management.
Bibliographic record
Abstract
Reviewed byYvan PETITUniversity of Quebec at Montrealpetit.yvan@uqam.ca SOME BASIC FACTSThis collective work by 43 authors is composed of a total of 19 chapters, including the introduction by the four editors. These are spread across 541 pages including illustrations. No index is provided. The authors come mainly from Europe and North America and are known names in the fields of project management, product management, organization studies, strategic management, and innovation. This is the 28th volume in the series “Advances in strategic management”. Previous volumes touched upon: globalization (vol. 27 – reviewed in vol. 14, n°2 of M@n@gement), economic institutions (vol. 26), network strategy (vol. 25), real options (vol. 24), ecology (vol. 23) and strategy process (vol. 22). The publication consists of five parts (each containing three to four chapters) entitled respectively: I) “Definitions and Connotations”, II) “Temporary Structure and Permanent Learning”, III) “Projects, Innovation and Capabilities”, IV) “Projects and Networks”, and V) “Toward Future Research”.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.053 | 0.045 |
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".