Ten Months, Seven Countries, Two Students, One Grant: Adventure Learning Grant
Bibliographic record
Abstract
What links a South American bluegrass band, racial inequities in South Africa, and Indian street food? Richard Vinh and Le'Ana Freeman will share their experiences first hand living in foreign lands and all the complications that follow. They will examine the life of a traveler and how they connected with communities through education, music, and food. Le’Ana taught children in South Africa and travelled through India discovering new definitions of personal identity and racial politics. Richard travelled through five South American countries studying urban planning and ultimately becoming the most famous banjo player in Buenos Aires. Valued Co-sponsors of Fairhaven College’s Winter 2016 World Issues Forum: Border Policy Research Institute, Canadian American Studies, Center for Law, Diversity & Justice, International Studies, Departments of Anthropology, History, Political Science, Sociology, Women, Sexuality and Gender Studies, WWU Diversity Fund, Ethnic Student Center, Whatcom Community College, Whatcom Peace & Justice Center, Veterans for Peace Chapter 111, Voices for Middle East Peace. About the Lecturers: Le'Ana Freeman is a world traveler, writer, food enthusiast, and make up artist. She is a senior at Fairhaven College studying Human Rights with an emphasis in Racial Identity and Colonialism; conducting several research projects abroad studying race and contemporary social issues in India, South Africa, and Thailand. Le'Ana Freeman received the prestigious 2014-15 Fairhaven Adventure Learning Grant and traveled to India and South Africa to study civil rights, resource mobilization and social movements, as well as life in post independent societies. Freeman is now working on her first book publication while working to motivate students of color from marginalized backgrounds to travel and share their stories with the world as diverse Americas. Working for Student Outreach Services an administrative assistant and peer mentor. Richard Vinh is a Fairhaven senior studying sustainable community development through architecture and law. He spent the past year in South America on the Adventure Learning Grant working with children, and discovering the South American folk experience. Born and raised in Seattle and Bellingham, his interests bounce between banjo plucking, rock climbing and writing flash fiction.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.022 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.248 | 0.130 |
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".