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Record W3096440250 · doi:10.5539/ass.v16n11p56

The Impact of Exposure to the Game of Thrones on Saudi Male Identity

2020· article· en· W3096440250 on OpenAlexvenueno aff
Merfat Alardawi

Bibliographic record

VenueAsian Social Science · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsDramaPsychologyIdentity (music)Perspective (graphical)AdvertisingSocial psychologyArtAestheticsLiteratureVisual arts

Abstract

fetched live from OpenAlex

The objective of this study is to examine the impact of Game of Thrones on the cultural identity of young Saudi males. The study also discovered the reasons why Saudi males watch American TV series (Game of Thrones) from a critical cultural perspective. This study has collected the data using an online survey conducted on 63 Saudi male adolescents with age ranging from 15 to 25 years who regularly watched Game of Thrones. The results show that the cultural identities of Saudi males are not negatively impacted because there are only limited viewers of this American drama series. The result reveal that 81.0% participants have watched Game of Thrones “alone” but only for having fun, learning a new culture and passing time. The relationship between age, education with respect to time spent on watching Game of Thrones and respective opinions are statistically significant. The study concluded that learning English language, acting like characters of the drama series and watching their favorite actors and actresses are the main motives of watching this TV series.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.042
GPT teacher head0.371
Teacher spread0.329 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

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