Gaining Entrée into a Micronesian Islander-Based Community Organization Through Culturally Responsive Team Building and Reflection
Bibliographic record
Abstract
Building trust and rapport is crucial in developing sustainable relationships with communities of color who have suffered historical trauma (Nguyen-Truong, Closner, & Fritz, 2019; 1Nguyen-Truong, 1Leung, & Micky, 2020a). A history of nuclear weapons testing by the United States in Micronesia, and subsequent ill-prepared cleanup efforts, has created a historical trauma for the Micronesian Islander community (Letman, 2013). The purpose of this brief article is to describe a critical foundational engagement project approach when gaining entrée into a Micronesian Islander community-based organization to co-develop the culturally relevant main project to improve rates of Micronesian Islander enrollment in early childhood learning (ECL) programs. Building a sustainable community-academic partnership through culturally responsive team (CRT) building and leveraging the collective strengths, to address a community need, took half a year for relationship building, and shared decision-making.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".