Teaching Student-Centred Podcasting: Practice-Based Research and Relational Ethnic Studies in The Alchemist Manifesto Podcast "The Seeds, the Soil and the Cyber Garden" Series
Bibliographic record
Abstract
This essay, along with an accompanying podcast, outlines the goals, pedagogy, and implications of the Alchemist Manifesto Podcast’s three-part special series entitled “The Seeds, the Soil and the Cyber Garden.” We argue that podcasting that centres practice-based research can produce heartfelt, communal, and compassionate digital holistic interventions within and beyond the physical spaces of universities and their itinerant knowledge production and distribution. Based on the cross-campus collaboration between CSU Fullerton and CSU Los Angeles in the spring of 2022, we discuss the collaborative pathways generated by working with graduate students Nancy Ocana, Rosa Maldonando, Diana Ponce, Karla Hernandez, Gregory Esparza, Pedro Reyes, Susana Tapia, Felicia Mora, Pedro Martinez, Francisco Najera, Katherine Batanero, and Caroline Romero. Additionally, the essay outlines the series, which features conversations with contributors Roderick Ferguson and Anita Tijerina-Revilla, and our collective efforts to situate podcasting within critical university studies and relational ethnic studies.
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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 | 0.017 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.027 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".