Leading Students and Teachers Away from Adversity and Towards Success
Bibliographic record
Abstract
There are nearly 3000 "Leader in Me" schools throughout the world and the hallmark of this transformational leadership program is developing student leaders. This proposal aims to share the best practices implemented and experienced through this innovative process that has helped to increase gains in students, especially those deemed at-risk. The session will NOT be promoting a particular product but rather facilitating the sharing of ideas and strategies for developing student leaders. Using engaging protocols and proven exemplars from schools throughout the country, this proposal will share the activities school leaders and teachers can infuse to encourage students to become leaders in the classroom and the community. School spotlights will include AB Combs magnet in Raleigh, NC based on their exemplary practices including: Celebrate Success Assemblies: Celebrate Success Assemblies are special assemblies held at the end of every quarter after report cards go home and are designed to spotlight the achievements of our students CHILDREN'S CHAT Children’s Chat is a time when student representatives from all grade levels can meet with school administration to discuss student issues and concerns. \nLEADERSHIP DAY Twice a year (in the fall and spring) educators from all over the world come to learn about our school. Students greet our guests, present flags from countries that are represented at A.B. Combs, give speeches, showcase their talents, present data notebooks, and share their experiences. The visiting educators learn from our students and staff what makes our leadership model so special Cultural Arts Assemblies: Each year, all students have the opportunity to experience 4-5 arts performances from a range of professional artists, including actors, musicians, dancers, and storytellers.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.016 |
| Scholarly communication | 0.021 | 0.007 |
| Open science | 0.001 | 0.024 |
| Research integrity | 0.002 | 0.010 |
| Insufficient payload (model declined to judge) | 0.012 | 0.008 |
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".