Social Displacement in the Cyberworld Era as Presented in Nikesh Shukla’s Meatspace
Bibliographic record
Abstract
Social displacement refers to the feelings of alienation and isolation one experiences while living among others. Today, many have adopted new lifestyles in their quest for recognition, and technology is playing a significant role in this transformation. This paper examines the topic of the impact of technology and its role in distancing individuals from genuine physical connections. By analyzing the behavior of Kitab, the protagonist in Nikesh Shukla’s Meatspace, the study aims to understand how social media as a form of technology has affected individuals. Using an interpretative method, the study also examines how superficial social norms shape identity development. It highlights the destructive effects of the excessive use of social media, which contributes to social displacement. By adopting a comparative perspective, the study delves into shared concerns related to identity formation within a fragmented digital world. Hence, the study, while encouraging a deeper engagement with Meatspace and its implications, suggests further studies on the topic as technological advancements and the dominance of cyberspace increasingly take control of individuals’ identity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.026 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".