13. Speculative futures for higher education: weaving perspectives for good
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
Using a speculative future use case, and a three-part multiple author format, this chapter creates a container for a conversation amongst co-authors representing various roles including online students, faculty, and administrators, regarding a change in teaching and learning. In doing so, the chapter attempts to cross theory-practice-policy lines to provide a contextualized, systemic examination of a possible iteration of higher education. The aim of this effort is to grapple with the question of ‘goodness’ given a specific context and situation, rather than with the question of ‘goodness’ in universal terms. Through the response from co-authors, and the analysis and synthesis that follows, this chapter aims to problematize the universality of what it means for futures to be “good,” highlight the messiness of speculative futures, and make visible the ways in which roles, values, identities, ideologies, and systems shape the ways in which learning futures are perceived to be “good.”
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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