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Record W2605452461

The Influence of Home Movies on the Dressing Pattern of Students: A Study in a Nigerian Public University

2017· article· en· W2605452461 on OpenAlexvenueno aff
Oberiri Destiny Apuke

Bibliographic record

VenueCross-cultural communication · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMedia, Gender, and Advertising
Canadian institutionsnot available
Fundersnot available
KeywordsSimple random sampleSample (material)Data collectionPsychologyAdvertisingMedical educationVisual artsSociologyArtMedicineSocial science
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACT This research work set out to examine the influence of home movies on the dressing pattern of students of tertiary institutions. The researcher employed simple random sampling to select 152 students from Taraba State University, Jalingo which formed the sample size. Questionnaire and interview were used as the instruments for data collection. Data gathered were presented using tables while frequency counts and simple percentages were used for analysis and interpretation. The research work among many things reveals that virtually all the respondents’ watches television and they do so very often. The study also revealed that youths imitate the hip hop/hippies and makeup/hairstyles projected by home movies than any other form of dressing and the major reasons for that are for fashion and imitating a role model as the study postulates such act makes them look indecent on campus. Reversing this issue, the study recommends that media and film regulatory frameworks must continue to be vigilant in screening contents of home movies so as to ensure the preservation of Nigerian/African cultural values both in the content and costume of these home movies. Keywords: Home movies, Influence, Students, Dress pattern, Taraba state university, Jalingo.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.073
GPT teacher head0.402
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 teacher head, not a consensus.

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
Published2017
Admission routes1
Has abstractyes

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