Stepping Out: Dare to Step Forward: Step Back, or Just Stand Still and Breathe
Bibliographic record
Abstract
It is important to step out and make a difference. We have one of the most unique and diverse professions that allows for diversity in thought and practice, permitting each of us to grow in our unique niches and make significant contributions. I was frightened to 'step out' to go to culinary school at the age of 46, but it changed forever the way I look at my profession and I have since experienced the most enjoyable and innovative career. There are also times when it is important to 'step back' to relish the roots of our profession; to help bring food back into nutrition; to translate all of our wonderful science into a language of food that Canadians understand. We all need to take time to 'just stand still and breathe': to celebrate our accomplishments, reflect on our actions, ensure we are heading toward our vision, keep the profession vibrant and relevant, and cherish one another.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.026 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.008 | 0.021 |
| Insufficient payload (model declined to judge) | 0.027 | 0.017 |
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".