Bibliographic record
Abstract
The last two decades following the Islamic Cultural Revolution have led filmmakers of the New Iranian Cinema to disguise social commentary in film through myths and metaphors. This study highlights the very beginnings of women’s changing roles from being sexual objects of minor interest to becoming subjects of prominent scrutiny in a feminist filmmaker’s film, The Legend of Sigh. Five parallel but alternating stories bring together the dilemmas of five women from different strata culminating in the binding paradox of their lives. It is within this paradox that the role of Sigh, as a duality of the masculine and feminine, is examined as the touch point of the subversive and collaborative layers of the film. A character analysis determines how female representations are structured across power discourses, particularly wielding results of how the technology of power and state ideology shapes female subjectivity by transforming the female voice into sites of resistance. Resistant measures are cited as cries for either initiation into individuation or liberty from the patriarchal norm. The causal motivation behind that resistance is what links the women and their contexts together within the plot. They are all equally either abused or abandoned by the norm in power. Despite the struggle to empower their identity through the maternal guise of Sigh, his paternal guise succeeds in elevating the female voice by confining it to the space of the other.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".