Identity of Successful Women: An Analysis of Transitivity System and Stance Markers in Selected TED Talks
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".