Applying the ‘Social Turn’ in writing scholarship to perspectives on writing self-efficacy
Bibliographic record
Abstract
The aim of this paper is to explore the fit between the cognitive concept of writing self-efficacy and a socially constructed epistemology of writing. Socially constructed perspectives on writing emphasise context and community and include academic literacies, rhetorical genre theory, and the writing across the curriculum movement. These perspectives have been prominent in theoretical discussions of writing since the 1980s. This paper argues that the measurement of writing self-efficacy has continued to prioritise assessing writing self-efficacy as ability to successfully accomplish superficial writing product and process features, while the social context of writing and its resultant impacts on the identity forming, relational, emotional and creative impacts on writing self-efficacy have been largely ignored. The historical context of paradigmatic shifts in writing theory will be discussed with a lens towards proposing a synthesis of three constructionist situated perspectives - activity theory, rhetorical genre theory, and communities of practice - and how these situated perspectives may inform a more complete view of how writing self-efficacy should be assessed and measured. How practitioners may consider the merger of these theories in writing pedagogy will be introduced to inspire future research.
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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.002 |
| Science and technology studies | 0.007 | 0.057 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".