Socializing the Digital: Taking Emic Perspectives on Digital Domains
Bibliographic record
Abstract
There is a tendency in scholarship on new and digital literacies to disassociate subjectivities and contexts from analyses and to generalize practices. This Language and Literacy special issue redresses such a tendency by exploring digital domains from agentive positions and from contextual perspectives. With submissions from scholars around the world, we have come together to socialize, even personalize, the digital to locate technologies in place (Prinsloo & Rowsell, 2012). For us, literacy teaching is most powerful when digital technologies and new media in formal and informal contexts are viewed as placed and as agentive. Traditionally literacy has been viewed as a repertoire of skills that individuals use to do something. Often seen as an inventory of skills such as speaking, listening, communicating, reading, and writing, literacy was cast for some time as a set of autonomous schooling practices (Street, 1984). When the social turn in literacy took place (Gee, 1996), literacy became viewed as shaped by contexts in which they occur. Brian Street describes this socializing of literacy as an ideological model of literacy, that is, literacy is shaped by context, power and history (Street, 1984). For example, literacy
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".