Women Dealing with Shame through Story, Dialogue & Drama Techniques
Bibliographic record
Abstract
“I’m not enough,” says the woman covered in shame. For women, shame looks like a web of unattainable expectations based on identity, as found by Dr. Brene Brown in her recent research (“Shame Resilience Theory” 46). Shame is her inability to maintain societal expectations on appearance, living in a broken home, or thinking she isn’t smart enough. Throughout my undergrad I’ve learned what drama can do, and after making that list, I found that my only remaining question was ‘Can drama help people deal with shame?’ My research will seek to answer: “How can using dramatic methods such as; story, dialogue, and Play Back Theater help female university students to explore and overcome feelings of shame?” My goal is to utilize narrative inquiry, dialogue, and the techniques of Augusto Boal’s Theatre of the Oppressed to help undergraduate women gain self-awareness and healing in terms of their personal shame. Utilizing a mixture of qualitative and quantitative research I’m going to run 3-5 exclusive Play Back Theatre sessions – a style of theatre that involves sharing the stories of audience members and retelling them in theatrical ways - for 10-15 participants during the winter semester. I will use prior and post questionnaires, and focus group meetings for dialogue to obtain my results. This research question is important because if shame fuels disconnection and drama promotes connection, then I want to find out if these ‘therapeutic’ aspects of drama can help women explore and overcome shame in their lives. If my research is successful, some desired outcomes are that the women feel heard and helped, as well as the findings be used to help other educators guide women through their shame by utilizing these drama techniques. The program may also be integrated into curriculum outside of psychotherapy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".