The rainbow bridge metaphor as a tool for developing accessible e-learning practices in higher education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper explores the extent to which existing accessibility metaphors can help to develop our conceptualizations of accessible e-learning practice in higher education and outlines a proposal for a new rainbow bridge metaphor for accessible e-learning practice. The need for a metaphor that reflects in more depth what we are beginning to understand about how to how to bring about that change, who should bring about that change, and what the result of such a change might be is identified. One such metaphor that could help us do this is the metaphor of a rainbow bridge. The stakeholders of accessible e-learning within higher education may understand the rainbow bridge as a useful metaphor in that the colours of the rainbow can represent all the main stakeholders in accessibility; the different views that different people can have of the same rainbow can represent different but related views of accessibility; and crossing the rainbow bridge to higher awareness can represent the awareness that is required in order to develop accessible e-learning practice.
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.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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 it