Bibliographic record
Abstract
I wrote ‘Narrative and Nature: Unsustainable Fictions in Environmental Education’ in 1991 as a revised version of a paper subtitled ‘Poststructural Inquiries in Environmental Education’ that I presented at the Sixth National Conference of the Australian Association for Environmental Education in September 1990. To the best of my knowledge, these papers were the first instances of advocacy for poststructuralist analyses of dicourses/practices in the Anglophone literature of environmental education. The key influences on my thinking at this time were US and Canadian ‘reconceptualist’ curriculum scholars, including Cleo Cherryholmes, Jacques Daignault, William Doll, Clermont Gauthier, Rebecca Martusewicz, William Pinar and William Reynolds. The significance and impact of my poststructuralist inquiries in environmental education were recognised by the award of the inaugural Australian Museum Eureka Prize for Environmental Education Research in 1997. Since then, my ‘post’ scholarship has expanded to include postcolonialism and posthumanism. Narrative continues to be an important theme in my work, especially through my development of an approach to narrative experimentation that I call ‘rhizosemiotic play’.
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.
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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.015 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.016 |
| Insufficient payload (model declined to judge) | 0.017 | 0.007 |
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".