Exploring the Eco-Psychological Impact of Hyper-Technologized Environments and Ecological Destruction in Anil Menon’s The Beast with Nine Billion Feet
Bibliographic record
Abstract
This paper delves into the intricate relationship between human beings and Earth's ecosystems, emphasising their mutualistic reliance on survival. However, contemporary challenges, characterised by excessive resource exploitation and the rise of hyper technologized environments, have resulted in a significant disconnect between humans and nature. This disconnection has precipitated various psychological issues and severed vital bonds between individuals, obstructing adherence to fundamental humanistic principles. Focusing on Anil Menon's book, The Beast with Nine Billion Feet, this paper operates within the framework of eco-psychology, utilising Richard Louv's concept of Nature Deficit Disorder to investigate the widening chasm between humans and nature. Ethical dilemmas, especially concerning the impact of AI and synthetic life forms, have also been explored in this context. The research objective was to unravel the unintended eco-psychological consequences resulting from excessive resource exploitation and an overemphasis on artificial environments. Employing a narrative method, this paper analyses plots, characters, and situations to illustrate this eco-psychological crisis. The main findings underscore Menon's portrayal of characters, showcasing innate human instinct to forge a profound connection with nature. Those residing in proximity to nature lead fulfilling lives, whereas individuals isolated from the environment exhibit varying degrees of Nature Deficit Disorder, compelling them to seek solace in nature.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".