Existing in hyperliminality: supporting educational developers with complex cross-disciplinary portfolios
Bibliographic record
Abstract
This opinion piece discusses educational developer portfolios that have cross-disciplinary or cross-service area reporting structure and responsibilities within an institution. It will outline some of the common barriers for these kinds of portfolios and highlight how often these barriers can be built into the administrative structures that already exist at an institution. It also suggests ways that reporting and administrative structures could help support a more holistic view of pedagogical development with more intentionality in the design of the role, that in turn will support a trauma-informed approach to this work, because without intentional support, cross-disciplinary roles can create trauma responses in educational developers. The piece ends with three recommendations that can be put in place to help support success and mitigate some of the tensions found for those who are in these types of cross-disciplinary roles.
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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 | 0.035 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.015 | 0.019 |
| Open science | 0.005 | 0.030 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".