WHY GEN-Z ARE FORGETTING THEIR CULTURES AND TRADITIONS
Bibliographic record
Abstract
This research paper examines the ways in which Western culture is affecting Generation Z (Gen Z), the demographic cohort born between the mid-1990s and the early 2010s.Western culture refers to the social norms, beliefs, values, customs, traditions, and practices that have developed in Western countries, including the United States, Canada, Europe, Australia, and New Zealand.As Gen Z grows up, they are being increasingly exposed to Western culture through various media, such as music, movies, television shows, social media platforms, and more.This paper discusses the impact of Western culture on Gen Z in various aspects such as fashion, social media, values, and attitudes.Western fashion and style have influenced Gen Z's clothing choices, with many young people around the world wearing Western-style clothing.Social media has become a central part of Gen Z's social lives, with platforms like Instagram, TikTok, and Snapchat shaping how they communicate and interact with each other.These platforms are largely driven by Western culture, with Western influencers and celebrities often setting the trends and influencing the content that is shared.Furthermore, this paper examines how Western culture has influenced Gen Z's values and attitudes towards gender, sexuality, race, and identity.Gen Z is more accepting and tolerant of diversity, with many young people embracing progressive social movements such as LGBTQ+ rights and racial equality.The paper discusses the potential benefits and drawbacks of this cultural influence, and how it might shape the future of this generation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".