Assessing Multiliteracies: Mismatches and Opportunities
Bibliographic record
Abstract
While current literacy theories acknowledge the sociocultural and sociopolitical dimensions of literacy learning and teaching, that is, multiliteracies, there exists a gap between theoretical approaches underpinning literacy teaching and assessment. In this dialogue, we re-enact this divergence by collectively defining multiliteracies and deconstructing assessment practices, while speculating on possibilities for reconstruction. Constructing this dialogue across multiple areas of expertise exemplifies multiliteracies because we use critical speaking, listening, writing, reading, and representing, to make sense of our new understandings, and showcase our knowledge construction. Our goal is to explore ways to translate the theories of multiliteracies into assessment practices that make visible children’s cognitive-psychological, psycholinguistic, sociocultural, and sociopolitical processes with all kinds of texts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.087 | 0.163 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.018 | 0.034 |
| Open science | 0.004 | 0.024 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".