INTERVIEW WITH PHILIP SMITH, CHAIR OF THE L. M. MONTGOMERY INSTITUTE
Bibliographic record
Abstract
This text aims to present an interview with Dr. Philip Smith, professor of Psychology at the University of Prince Edward Island (UPEI) and chair of the L. M. Montgomery Institute (LMMI). The L. M. Montgomery Institute, located in Charlottetown, Canada, provides a dynamic research center focused on the life and work of the Canadian author L. M. Montgomery (Lucy Maud Montgomery). Montgomery is best known for her book Anne of Green Gables, published in 1908 by the L. C. Page Company. She also wrote twenty novels, an autobiography, and hundreds of short stories and poems. The LMMI, founded in 1993 by Dr. Elizabeth Epperly, has been dedicated to promoting research into the life, work, and culture of L. M. Montgomery. This interview results from a training program conducted at the University of Prince Edward Island, with funding provided by the CAPES Foundation (Process n.: 88887.838993/2023-00). Keywords: L. M. Montgomery. L. M. Montgomery Institute. Philip Smith.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 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".