Bibliographic record
Abstract
Epistemologies, ontologies, and education based on colonial Eurocentric assumptions have made animism difficult to explicitly explore, acknowledge, and embody in environmental research. Boundaries between humans and the “natural world,” including other animals, are continually reproduced through a culture that privileges rationality and the intellectual as primary ways of knowing, even though they have been repeatedly acknowledged as not enough to address increasingly pressing environmental concerns. I use my own doctoral research journey to explore possible methods for working with nonhuman “persons” as co-participants in, rather than objects of, research. Through the identification and use of a dialogic methodology and methods, I show how animism, as an enacted epistemology, can be incorporated into an approach to research and its representation in multi-media hypertext. By engaging animism as a paradigmatic framework for research, environmental educators can respond to repeated calls for epistemological diversity, and more significantly, make use of research approaches that support the explicit acknowledgement of other-than-human contributors to knowledge-making. Resume Les epistemologies, les ontologies et l’education fondees sur les presomptions coloniales eurocentriques ont rendu difficiles l’etude, la reconnaissance et l’expression explicites de l’animisme dans la recherche environnementale. Les frontieres entre les humains et le « monde naturel », y compris les autres animaux, sont constamment representees a travers une culture privilegiant la rationalite et l’intellectualite en tant que principales facons du savoir, bien qu’elles aient souvent ete designees insuffisantes pour cerner les questions environnementales de plus en plus complexes. Je me sers de mon propre cheminement de recherche doctorale pour examiner les methodes de travail possibles avec les « etres non humains » participants a ce titre a la recherche, plutot qu’a titre d’objets de la recherche. Par l’identification et l’emploi d’une methodologie et de methodes dialogiques, je demontre comment l’animisme, en tant qu’epistemologie designee, peut etre integre dans une approche de recherche et sa representation dans un hypertexte multimedia. En recourrant a l’animisme a titre de paradigme de la recherche, les educateurs en environnement peuvent satisfaire des exigences repetees de diversite epistemologique, et surtout, adopter des approches de recherche qui appuient la reconnaissance explicite de contributeurs autres que les humains a l’elaboration du savoir.
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 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 | 0.002 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".