Bibliographic record
Abstract
The only rival to Harrison McCain’s entrepreneurial success was his deep attachment to his Maritime roots. From McCain’s beginnings in Florenceville, New Brunswick, the early mentorship he received from K.C. Irving, to the global success of his corporate empire McCain Foods, Donald Savoie presents a compelling and candid biography of one of the most famous and down-to-earth figures in Canadian business history. Savoie, a longtime friend to McCain, describes a driven, charismatic, and energetic man who had a keen wit and a deep commitment to his business and hometown. Through unprecedented access to McCain’s papers and interviews with family members, friends, and colleagues, Savoie details the decisions that McCain made alongside his brother and business partner, Wallace McCain, from the company’s humble beginnings to its expansion in Europe, Australia, India, and China. McCain saw the potential of globalization before others did. Despite conflict between the brothers and the eventual fracture of their partnership, Savoie presents the McCains’ dedication as so immersed in the development of their company that they had little time left for second-guessing. At a time when New Brunswick struggles to reinvent itself economically, Savoie points to former government policies and programs that helped the company thrive and holds up the example of Harrison McCain with the hope of seeing Canadian success stories like this in the future.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.324 | 0.118 |
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".