MétaCan
Menu
Back to cohort
Record W2918012480 · doi:10.5539/ijel.v9n2p229

Sex- and Age-Based Approach to the Study of Interruption in “The Kings of Summer” Movie and “Pretty Little Liars” TV Series: A Case of Same-Sex Teenage Interactions

2019· article· en· W2918012480 on OpenAlexvenueno aff
Eman Riyadh Adeeb, Amthal Mohammed Abbas

Bibliographic record

VenueInternational Journal of English Linguistics · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsnot available
Fundersnot available
KeywordsScripting languagePsychologyTelevision seriesCore (optical fiber)Developmental psychologySocial psychologySociologyComputer scienceMedia studiesTelecommunications

Abstract

fetched live from OpenAlex

The study is an attempt to investigate sex and age as crucial factors in the world of interruption. These two factors are investigated theoretically and then practically in two works, “The Kings of Summer” movie and “Pretty Little Liars” TV series. The two works are selected in terms of their compatibility with the core of the study; the characters are teenagers and of the same sex. The study adopts an adapted model to analyze interruption performed by teenagers with special focus on same-sex conversations. The two works’ videos were watched and listened to and then their scripts were precisely examined for more reliable results and judgments. The findings demonstrate that teenagers are characterized by their frequent and numerous interruption. Teenage male speakers are more pleased and relaxed to speak and practice interruption with peers (teenage male speakers). Interruption is also familiar in teenage female-female interaction.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.340
Teacher spread0.301 · 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 designQualitative
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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of English LinguisticsSame topicDigital Games and MediaFrench-language works237,207