Mentor, Scholar, Academic, and a Massage Therapist: an Interview with Amanda Baskwill, PhD(c), MSc, RMT
Bibliographic record
Abstract
Amanda Baskwill, PhD(c), RMT is influencing the massage therapy profession from seemingly all angles; she is a researcher, massage therapist, educator, innovator, and mentor. Baskwill previously was a full-time faculty member at Humber College in Ontario, Canada, and now holds the position of Associate Dean in the Allied Health School of Health Sciences at the same institution. She has published widely on research centered on the massage therapy profession, as well as the safety and effectiveness of massage therapy as a treatment for various conditions. This interview explores the development, career, and research of the innovative educator and scholar, Amanda Baskwill.
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 | 0.016 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.015 | 0.017 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".