Funds of (Difficult) Knowledge and the Affordances of Multimodality: The Case of Victor
Bibliographic record
Abstract
Drawing on semi-structured� interview� data,� this� paper� examines� one� man's� multimodal� engagement with the emotionally difficult aspects of his Chilean heritage. It builds on recent work (e.g., Marshall & Toohey, 2010) that has begun to unearth the intersection between funds of knowledge (Gonzalez, Moll, & Amanti, 2005), difficult knowledge (Britzman, 1998, 2000), multiliteracies (New London Group, 2000), and multimodality (Kress, 1997) in an attempt to call attention to the shifting nature of what is considered� about� difficult� knowledge,� and� to� the� role� of� multimodality� in� both� accessing� and� making� sense� of� the� difficult� in� one's� funds� of� knowledge.� The� analysis� reveals� that� young� people� might� be� purposefully kept away from punctuations on their community's� semiotic� chain� that� are� deemed� difficult� (e.g., images, documentaries) not only by schools, but also by family members for whom such punctuations invoke painful memories. The paper concludes with a call to teachers to be ever mindful of reproducing knowledge hierarchies in their classrooms, which may be partly mitigated by discussing the affordances� and� challenges� of� drawing� on� students'� funds� of� (difficult)� knowledge� with� families� and� communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".