COMMUNITY VOICES Transformational Leadership Without Equality Is Neither: Challenging the Same
Bibliographic record
Abstract
has worked in outdoor recreation, leadership development, wilderness therapy, and non-profit management. Her research focuses on predictors of positive health outcomes for marginalized female adolescents, leadership interventions that optim ize health and enable civic engagement for young women, and social policies that help and hinder the health and leadership opportunities for young women. This paper reports on my experience in the 2004/2005 University of New Brunswick sponsored 21 Leaders initiative, on the presentation of the initiative by me and a colleague at an international conference-W omen as Global Leaders- and on the capacity of 21 Leaders to contribute to transformation in New Brunswick. Résumé Cet article rapporte mon expérience en 2004/2005 à l'occasion de l'initiative 21 Leaders, parrainée par la University of New Brunswick, sur la présentation qu'une collègue et moi avons faite sur l'initiative lors d'une conférence internationale-W omen as Global Leaders- et sur la capacité de 21 Leaders de contribuer à la transformation au Nouveau-Brunswick.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.022 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".