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The Process
Published in R. Annie Gough, Injury Illustrated, 2020
After the testifying expert review, the doctor's modifications or additions will be finalized and the illustrations are considered complete. If the case does not settle, the illustrations are often produced as demonstratives with the disclosure of designated experts. Illustrations are then submitted into court at the discretion of the judge. I have seen a judge allow all of the illustrations, both prints under the elmo and slides presented on screen, during opening and closing and with experts on the stand. I have also watched a different judge in the exact same courthouse allow only five images from a chronology of 50 slides, and only those individual slides were allowed to be on screen during direct questioning and then immediately removed from view. Even though the litigation team and experts were not allowed to give narrative with the full chronology of visuals, the slides that were allowed still told the story. For example, this spinal surgery illustration was allowed by the judge, even though all of the surgeries leading up to this moment were not.
Women and the AIDS Memorial Quilt
Published in Nancy L. Roth, Linda K. Fuller, Women and AIDS, 2014
Clarice’s panel depicts an angel floating with several balloons. Three small balloons contain images of Sesame Street characters. Clarice was cremated with a stuffed Elmo toy, her favorite of the characters. The silver balloon in the upper left corner contains a photo transfer image of Clarice with quilted angel wings sewn to her shoulders. The balloon next to it has a photograph of Clarice and her mother that was taken when they moved in with Kathy; the words “Mother and Daughter” appear underneath it. Another balloon depicts two unicorns in needlepoint that Annie had stitched before she died. Kathy and her mother chose this image because it reminded them of a mother and daughter. When Clarice was sick, it was often difficult to change her clothes. Kathy and Clarice, always involved in crafts, made a Barney T-shirt that tied in the back to facilitate simple clothing changes. The shirt constitutes another balloon. The final balloon has a drawing Clarice made of herself. A stick figure with a feeding tube coming from her stomach, it simply says “ME.” The word “LOVE,” written three times, appears in the lower left corner of the panel.
Hashtag Mania or Misadventures in the #ultrapsychic
Published in Studies in Gender and Sexuality, 2019
I chose the name Elmo from some deeply unconscious association to the character Elmo on Sesame Street. Elmo is a furry red monster with a falsetto voice who hosts a segment aimed at toddlers called “Elmo’s World.” Elmo typically refers to Elmo in the third person as “they” or simply as Elmo in a manner that irks Sesame Street traditionalists who protest that his trans pronouns put toddlers’ grammar at risk. Indeed, Elmo has quite manic aspirations. In a 1996 special feature, Elmo Saves Christmas when they discover that although Christmas can’t happen every day, it is “always good to keep the spirit of Christmas every day and every year in your heart.” Hats off to #Elmo. They really pack a punch when it comes to challenging our most cherished myth.
Detecting Intensity of Anxiety in Language of Student Veterans with Social Anxiety Using Text Analysis
Published in Journal of Technology in Human Services, 2023
Morgan Byers, Mark Trahan, Erica Nason, Chinyere Eigege, Nicole Moore, Micki Washburn, Vangelis Metsis
We found better results when working with transfer learning. Both of our models that used BERT and ELMo embeddings performed about the same in terms of accuracy, with our implementation of BERT earning a 50.2% (±8.0%) five-fold cross-validated accuracy, while ELMo earned a 47.8% (±6.9%) accuracy. A notable aspect of our results is that BERT outperformed every other deep learning model (Figure 6). This is likely due to the depth and size of the model (Devlin et al., 2018) compared to other embeddings like word2vec. As with most of our deep learning models, both of our transfer learning models struggled to overcome our imbalanced data set (Figure 3c and d).