Bibliographic record
Abstract
The nutrition and dietetics profession is neither diverse nor inclusive of Black, Indigenous, and People of Color (BIPOC), yet to achieve racial/ethnic diversity, equity, and inclusion (R-DEI), nutrition professionals (educators, preceptors, and professionals) need to understand and care about related issues. However, both a space and curriculum to educate professionals about R-DEI are lacking. Our aim was to understand how knowledge, actions, identity, and experiences are related to beliefs about R-DEI among nutrition professionals. We developed a 20-week curriculum about R-DEI topics using the Transtheoretical Model (Stages of Change) and Critical Race Theory. It was delivered in #InclusiveDietetics, a Facebook group, between January and August 2020. Pre- and post-intervention surveys were used to understand participants’ identities, experiences, knowledge, beliefs, actions, and opinions and analyzed using logistical regression, t-tests, and descriptive statistics. Knowledge (p<.05), experiences with racism (p<.01), and being a former Academy of Nutrition and Dietetics member (p<.05) were positively correlated with participants’ beliefs about R-DEI in dietetics (that is, more highly valued R-DEI) while actions were negatively correlated (p<.001). Significant increases in knowledge (p<.01) and beliefs aligned with R-DEI values (p<.01) were observed following the intervention, driven by increases in white participants. A significant increase in opinions aligned with R-DEI values was observed among BIPOC (p<.01), but not white participants following the intervention. The importance of a space for professionals to examine R-DEI is critical to achieve professional equity and the #InclusiveDietetics curriculum may be an effective tool to better align nutrition professionals with R-DEI values.
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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 | 0.006 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".