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Record W4389203719 · doi:10.5430/wjel.v14n1p350

Identity of Successful Women: An Analysis of Transitivity System and Stance Markers in Selected TED Talks

2023· article· en· W4389203719 on OpenAlexvenueno aff
Safaa Moustafa Khalil

Bibliographic record

VenueWorld Journal of English Language · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
FundersMajmaah University
KeywordsTransitive relationConstruct (python library)Dominance (genetics)Identity (music)ScarcityCertaintyPsychologySocial psychologyLinguisticsComputer scienceEpistemologyEconomicsAestheticsMathematicsMicroeconomics

Abstract

fetched live from OpenAlex

In recent years, as women continue to break through barriers and shatter glass ceilings, it becomes necessary to understand how they construct their identities as successful individuals. To fulfill this purpose, this research paper analyzed selected TED Talks delivered by five successful women entrepreneurs. The present study aims to unravel how women perceive success according to their personal experiences. The analysis is conducted in two phases. In the first, Halliday’s transitivity system was used. In the second phase, Hyland’s (2005) analysis of stance was applied to scrutinize the linguistic choices made by the speakers to construct and convey their identities as successful individuals. Results of data analysis revealed that with the prevailing use of material transitivity processes, successful women were able to present their experiences clearly. The dominance of self-mentions and scarcity of hedges revealed their confidence and certainty in their speech and their success experience as well.

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 score0.063
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.008
GPT teacher head0.250
Teacher spread0.242 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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