Bibliographic record
Abstract
Philip Delves Broughton is a journalist, management writer, and best‐selling author of two books. Philip was a journalist with The Daily Telegraph for ten years, latterly as Paris Bureau Chief (2002–04) before he took an MBA at Harvard, which became the subject of his first book, the best‐selling What They Teach You at Harvard Business School. Philip writes regularly for The Financial Times, The Wall Street Journal and The Spectator. From 2009–2010, he spent several months at Apple writing case studies for Apple University, its internal management program, and now works with The Kauffman Foundation for Entrepreneurship and Education. His most recent book The Art of the Sale: Learning from the Masters about the Business of Life is an ‘insightful scholarly treatise on sales’ with a global perspective on this critical business function.
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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.012 | 0.067 |
| Scholarly communication | 0.034 | 0.049 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".