<i>Salir Adelante</i>: Collaboratively Developing Culturally Grounded Curriculum with Marginalized Communities
Bibliographic record
Abstract
In this article we discuss a collaborative research project meant to ground community members’ voices in curriculum design. We argue that performing collaborative research with students and parents can better inform curriculum design decisions, particularly for communities whose identities, knowledge(s), and ways of being have been historically marginalized. Building from the culturally responsive curriculum literature, we have developed a culturally grounded curriculum development approach. We illustrate the approach through discussing a case of its development and implementation with an educational nongovernmental organization (NGO) that provides access to secondary school for Quechua (Indigenous) young women in Peru. This article reflexively reports the process of the NGO’s collaborative inquiry project to cocreate meaningful educational opportunities with the students and parents. We then discuss dilemmas of interpretation that arose when incorporating community voices into curricular decisions, and how the collaborative curriculum approach can apply to formal and nonformal learning spaces in other contexts.
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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 | 0.016 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".