Building as Interface: Sustainable Educational Ecologies
Bibliographic record
Abstract
This paper begins with the most obvious, and yet most elusive, of educational media ecologies, the buildings which are ‹home› to pedagogic communication and interaction, and considers how we might understand «building as interface», construed first as a noun, («a structure with roof and walls» – OED) referring to places as physical structures, and then as a verb, («the action or trade of constructing something» – OED), referring to the activities of construction through which we can engage technologies central to theory, research and practice. Our concern is with exploring the larger question of educational sustainability: with what ‹sustainability› means when applied to a specifically educational context, and with the sustainability of the kinds of emerging educational environments in which new information and communications technologies play a significant role. This question of sustainable educational environments is driven by a need to be responsible and accountable for the impact of the technologies and practices we eagerly embrace in the name of «21st century learning», even as prospects for a 22nd century are so rapidly receding from view. As one prominent media ecologist put the point: «we have to find the environments in which it will be possible to live with our new inventions» (McLuhan 1967, 124).
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.032 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".