The Intrinsic Values of Humans and Animals in Jack London‘s Novel The Call ofThe Wild
Bibliographic record
Abstract
This research discusses the relationship between humans and animals in Jack London's novel entitled The Call of the Wild using deep ecology approach. A dog named Buck was thrown into the harsh realities in Yukon during the Klondike Gold Rush. Buck transformation from a tamed animal into a wild animal is the focus of the novel. The themes of the novel are self- realization, intrinsic value, and ecological interdependence. This research reveals that Buck's trip is divided into three stages: home seclusion, adaptability to nature's hardships, and final harmony with the wild. This progression reflects a process of self-realization that showing how humans, animals, and ecosystems interacts with each other. The novel criticizes anthropocentric worldviews and highlights the significance of recognizing the intrinsic value worth of all living things. London's work offers philosophical insights into the human- animals relationship, demonstrating that ecological harmony is possible by recognizing nature's inherent worth. Buck's metamorphosis serves as a metaphor for humans‘ potential to coexist symbiotically with animals. The study takes a qualitative approach, with textual analysis based on ecocriticism and Arne Naess' deep ecology theory. The Call of the Wild is the primary source of data, while scholarly publications and pertinent literature serve as secondary sources. The analysis entails identifying key characteristics, observing their interactions with the environment, and applying deep ecology principles. The findings highlight the need of moving beyond human centric attitudes and recognizing the intrinsic value and connectivity of all life forms in developing a more balanced, empathic, and sustainable relationship with the natural environment.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.026 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".