Unsettling intimacies:Re-cognizing ecological relations with the work of Jean Clandinin
Bibliographic record
Abstract
For Jean Clandinin, narrative inquiry is not about being but becoming and as such posits knowledge as a continuous, non-teleological process rather than a static object. Experiential knowledge, for Clandinin, then, is intimately bound up with the vicissitudes of lived experience. If stories make meaning from experience, they open up an imaginative space through which researchers can come to understand experience as well as the knowledge that emerges from it or re-cognize such. Inquiring into experiential knowledge through narratives is valuable for research, and particularly for research that engages ecological crises, because it enables a more robust, nuanced view of life—both human and nonhuman—to emerge. Further, as Clandinin’s work reconfigures the role of the researcher, it unsettles hierarchical assumptions within the research space, allowing for collaboration, polyphonic texts, and reconfigured understandings to emerge. Clandinin’s work troubles dominant narratives about knowledge that presuppose conceptual reification and mastery. As such, narrative inquiry has the potential to support research that is interested in reconfiguring relationships between human and non-human “nature” in ways that do not necessarily fit into dominant narratives about knowledge in education. Using a framework informed by contemporary eco-criticism and trauma theory, I consider how narrative inquiry might offer reparative methods for educational research that engages ecological crises. As narrative inquiry aims to honour the particularity of experience and promote growth without assimilating plurality into an objective singularity, its methods have the capacity to provide insights into ecological relations that are critical, self-reflexive, and ethically responsive.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.015 | 0.061 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".