What's Troubling about the "Wilderness"?: Children's Literature and its Portrayals of Nature
Bibliographic record
Abstract
It is axiomatic that children’s literature functions as a window for children to understand and develop their understanding of the world around them. However, when it comes to fostering ecological citizenship, the understanding of the interconnection and interdependency of all lives and materials, there exists a glaring problem. Children’s books written from an anthropocentric point of view often portray nature, as the “other”, separate from or subordinate to humans, as mere resources or playground. For example, in Finding Wild, Megan Wagner Lloyd depicts nature as a pristine wilderness untouched by civilization, through the story of how two children leave the bustling streets—the environment of their everyday life—and enter an otherworldly land to find “Wild.” Whereas in children’s books by Native American authors, nature intertwines with humans and their everyday life. Embedded in this intertwining relation are more than mutual dependence and kinship between nature and humans. There is a sense of mystery and sacredness in nature, which is irreducible to resources for humans, who have reverence and responsibilities for the nonhuman. In this paper, I examine the implications and effects of representations of nature through the lens of ecocritical theories with a focus on Native American children’s books and tales by Wabanaki and Cree-Métis authors. My analysis seeks to emphasize the importance of introducing ecological views in children’s literature for cultivating ecological awareness and citizenship. I contend that the inclusion of children’s books by Native American authors in the K-12 curriculum is imperative for this purpose in facing challenges of urgent ecological crises.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".