Bibliographic record
Abstract
AbstractThe purpose of this digital story is to artistically share experiences of dietitians in Chicago and generate discussion of solutions for delivering nutrition care. Four Registered Dietitians (RDs), practicing in the city of Chicago for >/=5 years. All female. Dietitians were contacted via phone or email. Participating dietitian responses were recorded using a microphone connected to a password protected MacBook. Responses were edited for quality purposes in the program “Logic.” The finished product was edited on iMovie. Images and video were obtained from a google image search with criteria including “labeled for reuse.” “Bindi” believes the minimum wage in Chicago should be raised, therefore poverty would be reduced and Chicago clients would be able to prioritize their health. “Ana” believes a Spanish course added to dietetic student curriculum would involve students in the Chicago community. “Maria” noted the concern dietitians have working in unsafe neighborhoods in Chicago, but this should not prevent dietitians from helping people in need. “Suzanna” recommends networking with other Chicago dietitians to improve professional development. At the Sixth Annual Critical Dietetics conference in Granada Spain, attendees praised the film and reported experiencing similar challenges in their practice and professional isolation as a result. At the Diversity and Sustainability Conference at Dominican University in River Forest Illinois, 98% of attendees reported the content was engaging, 95% reported the presentation kept their attention, and 98% claimed the information provided was relevant and useful. In conclusion, the digital story reduced professional isolation by creating dialogue about challenges and opportunities for improvement for dietitians in professional settings. Further research is required to effectively study challenges faced by dietitians in Chicago to ways dietitians may thrive, despite working with impoverished populations.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.015 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".