Redesigning for mobile plurilingual futures
Bibliographic record
Abstract
The New London Group’s 1996 manifesto was a clarion call to educational researchers to fundamentally redesign language and literacy education for the needs of global learners communicating in evolving digital media environments. In this conceptual overview, the “how”, “what” and “why” of multiliteracies are critically re examined from the perspective of mobile digital language learning in posthumanist media ecologies, with attention drawn to paradigm shifts in language, technology, multimodality and context. We argue that Web 3.0 environments, AI and rapidly emerging algorithmic cultures have outpaced earlier critical theorizations of multiliteracies and digitally mediated learning practices as well as meaningful implementation of multiliteracies pedagogies in schools. We then reconsider the affordances and constraints of Web 3.0 tools for multilingual/plurilingual language learning, and sketch pathways for critical and productive engagements with mobile devices and multiliteracies pedagogies that reframe and advance the important critical work of the New London Group.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.010 | 0.019 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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".