Pedagogies of Possibility Within the Disciplines: Critical Information Literacy and Literatures in English
Bibliographic record
Abstract
While most disciplines have responded to the generic openness of the ACRL Standards by creating discipline-specific guidelines and competencies, there is a need for us to consider other ways to approach information literacy in the disciplines. Critical information literacy reminds us to engage ourselves and our students with what Freire described as "problem-posing education," which "bases itself on creativity and stimulates true reflection and action upon reality" (84). This article discusses how information literacy work in literatures in English could engage students and librarians in the act of collective problem-posing about the discipline. Drawing upon critical information literacy's emphasis on questions, this article argues for the importance of engaging our students, our colleagues, our campuses, our selves, and our profession in the act of questioning related to information literacy and the disciplines.
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 | 0.018 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.011 | 0.052 |
| Scholarly communication | 0.016 | 0.018 |
| Open science | 0.001 | 0.017 |
| 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".