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Record W4206139187 · doi:10.5539/ells.v12n1p42

The Commentary of City Promotional Films Based on Transitivity Theory: A Case Study of Xi’an and San Francisco

2022· article· en· W4206139187 on OpenAlexvenueno aff
Yihan Weng

Bibliographic record

VenueEnglish Language and Literature Studies · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTransitive relationConnotationPerspective (graphical)Style (visual arts)ExistentialismFocus (optics)Function (biology)SociologyMental processEpistemologyProcess (computing)LinguisticsPsychologyComputer scienceCognitionArtPhilosophyVisual artsArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

Based on Halliday’s theory of ideational function, this paper selects the commentary of city promotional films of Xi’an and San Francisco and analyzes them from the perspective of the transitivity system. The main purpose of this paper is to analyze the language skills of the two commentaries and to provide ideas and methods for the audience to understand such explanatory texts. This paper focuses on the following two questions: 1) How do the six processes of the transitivity system distribute in the two commentaries? 2) What are the specific functions of the six processes in the two commentaries? The results show that 1) there are two kinds of processes frequently used in explanatory texts, namely material process and relational process; 2) the frequency of mental, verbal and existential processes is relatively low; 3) behavioral process has no occurrence. The reason may be that although the textual structure and description focus of the two commentaries are different, they both belong to the applied style of oral explanation, so that they share the same social functions of shaping the city image, highlighting the city connotation and managing the city brand.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.014
Threshold uncertainty score0.907

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.014
GPT teacher head0.269
Teacher spread0.255 · 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.

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

Citations0
Published2022
Admission routes1
Has abstractyes

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