Returning ‘learning’ to education: Toward an ecological conception of learning and teaching
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 article describes a notion of learning as adaptive semiotic-growth. In line with the theme of this special issue, learning will be approached on a broad ecological and evolutionary continuum – most generally expressed as a form of adaptation to the environment. Viewing learning through the criterion of signification (semiosis) means that learning is continuous across the entire biological realm. Both the life process and the learning process are expressed through forms of semiotic-engagement and involve continual adaptation and meaning-making. Thus, learning cannot be seen as unique to humans. Learning is more broadly ecological before it is “cultural”. From here we can imagine educational institutions as forms of exaptation, that evolved naturally to channel learning more effectively. Thinking of learning on an ecological continuum means that learning cannot be “located” or pinned down easily in educational research or practice. Rather, learning has a sporadic identity; it is emergent in the specificity of events and must be discerned within the practices that enact it. Realizing learning as something emergently enacted in the educative encounter, and not something that can be determined and implemented, allows us to resist turning learning into an accountability tool that can easily be used towards ideological ends.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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