Mapping Territories and Creating Nomadic Pathways with Multiple Literacies Theory
Bibliographic record
Abstract
This article foregrounds Multiple Literacies Theory (MLT) positioned from a deleuzianguattarian perspective. It is a literacy paradigm different from prevailing territories such as New Literacy Studies and Multiliteracies. MLT deterrritorializes familiar literacy theorizing and is a complementary theoretical experiment to those conducted by curriculum theorists working with poststructuralist perspectives and complexity theory. It accompanies a deleuzianguattarian philosophy as a nonphilosophy for thinking about problems that present themselves in the world. In this case, we deploy MLT to create nomadic pathways as we consider vignettes from a research study on a child acquiring multiple writing systems simultaneously. The vignettes illustrate what literacies produce and how they function through the lens of MLT. MLT proposes that from the effect of investment in reading, reading the world, and self, a reader is formed and transformed in a process of becoming Other.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.008 | 0.016 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".