Posthumanist and Postcolonial Possibilities for Outdoor Experiential Education
Bibliographic record
Abstract
Background: Teaching and learning in outdoor experiential education is often conducted on lands with troubled histories of settler colonialism. This calls for new and creative forms of socioecological responsibility to attend to human supremacism and exceptionalism that marginalizes, exploits, dominates, and objectifies Other(s) in these Anthropocene times. Purpose: Through posthumanist philosophy (re)conceptualizing Western binary logics, this article explores possibilities for postcolonial land ethics in outdoor experiential education to address past, present, and future socioecological injustices and threats. Methodology/Approach: Adopting new materialist methodologies, this article examines affective materiality emerging from a series of multisensory researcher/teacher enactments, as set within pedagogies attuning-with land with a Grade 4/5 class in Canada. Findings/Conclusions: The affective materiality of sense-making in the researcher/teacher enactments provided opportunities to challenge discursively positioned land ethics, suggesting a transforming-with Other(s) through relationally co-constituted existences. Implications: Understanding that no separate and discrete worldviews exist in which individuals act through autonomous agency, but that worlding emerges through relational agency, teaching, and learning in outdoor experiential education can generate an intrinsic sense of responsibility to attend to more equitable relationships with Other(s) for/with/in these Anthropocene times.
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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 | 0.003 | 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 | 0.008 | 0.036 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".