At the Intersection of Selves and Subject: Exploring the Curricular Landscape of Identity
Bibliographic record
Abstract
Working with 16 Education scholars from international contexts, this project aimed to raise awareness of the inextricability of our teaching and learning selves and the subjects with whom and which we engage. By exploring identity at this intersection, we invited other educators to reconceptualise relationships with students, curriculum, and their varied contexts. Our hope is to encourage authenticity, consciousness, and criticality that will foster more liberating ways of teaching and learning. In encouraging other scholar practitioners to examine where self and subject meet, this symposium outlines how critical, creative, traditional, and arts-integrated approaches create spaces for currere. A celebration of both individual and collective findings, five of the 16 contributing scholars come together in this symposium to discuss the curricular landscape of identity. From our varied contexts, we consider the essential ethos of integrating self and subject.
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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.016 | 0.028 |
| Scholarly communication | 0.018 | 0.009 |
| Open science | 0.001 | 0.019 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".