‘What do we talk about when we talk about climate change?’: meaningful environmental education, beyond the info dump
Bibliographic record
Abstract
Abstract Learning about the causes and effects of human-induced climate change is an essential aspect of contemporary environmental education (EE). However, it is increasingly recognized that the familiar ‘information dump delivery mode’ (as Timothy Morton calls it), through which new facts about ecological destruction are being constantly communicated, often contributes to anxiety, cognitive exhaustion, and can ultimately lead to hopelessness and paralysis in the face of ecological issues. In this article, I explore several pathways to approach EE, beyond the presentation and transmission of ecological facts. I position my conceptual discussion around my own teaching experiences speaking about climate change with undergraduate students across several Education classes through 2019 to 2021. I situate these reflections within the current discourse on education and teaching in/for the Anthropocene. Throughout this discussion, I locate various ways in which much EE fails to contribute to student’s agency and empowerment by consistently reducing complex ecological phenomena to a set of problems, mainly economic/technological, to be fixed by technocracy. I propose that a contemplative–existential perspective to EE is capable of responding to these reductions, most basically by providing opportunities and practices for students to process their grief and other emotions through recognizing the Anthropocene as an inescapable reality, but also a reality that cannot be determinately imagined or predicted.
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 | 0.001 | 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 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".