Proliferation of Multi-Cultures Through Globalization: Is It Promoting the Indigenous Culture or Global Culture?
Bibliographic record
Abstract
The purpose of the study was to highlight the impact of multicultural proliferation through globalization on the adolescents of Lahore, Pakistan. A way to measure part of the impact is to have an understanding of how they have internalized foreign holidays and/or festivals which belong to other cultures. The data were collected from 200 male and female participants, of ages 13 to 19 years. The sample was subdivided into two groups of 100 participants each based on their parents’ income level and the type of their institution (public or private). The medium of instruction in the private institutions of Lahore is English. English is, clearly, the language of globalization. In this regard, the hypothesis is that those students who study in private schools are more affected than those who study in public schools and whose medium of instruction is Urdu. A survey design was used to collect data regarding their perceptions about foreign cultural and religious festivals such as “Christmas”, “Holi”, “Valentine’s Day”, etc. Hamelink’s Cultural synchronization theory provided the theoretical lens to the study. The analysis procedure was based on content analysis. The findings reveal a vivid difference between the perceptions of both groups. The adolescents who belong to the lower socio-economic status (who attend public schools) do not favour the celebration of foreign festivals. However, a tendency towards celebrating “Black Friday”, “Valentine’s Day” and “Basant” has been noticed. On the other hand, the adolescents of higher socio-economic background (who attend private schools) look forward to celebrating these festivals and perceive their celebration does not harm their cultural values. Even if this effect is partially due to globalization, the speedy influence on one stratum of the young generation of Pakistan may lead to a rapid assimilation to the global culture in the forthcoming times and also an opposition to the other strata. The study suggests a national media campaign as well as an institutional policy with an emphasis on indigenous cultural, social and religious values. There is a need to be more tolerant towards “others”, and know how to co-exist but at the same time be able to retain the elements of the home culture of Pakistan, rather than adopting foreign practices.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".