Inclusive Science Communication Approaches Through an Equity, Diversity, Inclusion, and Social Justice (EDISJ) Lens
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Science communication has taken center stage in Science, Technology, Engineering, and Math (STEM) disciplines in the context of public outreach and citizen science. Developing practical communication skills is imperative for all scientists to be highly successful in their careers and more so for underrepresented and Black, Indigenous, and People of Color (BIPOC) professionals in STEM. The program, led by the Engineering and Science Librarian at the University of Victoria (UVic) Libraries, aimed to equip students and early career scientists with critical communication skills by leveraging the unique voices and lived experiences of BIPOC speakers in STEM disciplines. Through this program, a unique toolkit with engaging modules consisting of 30 short videos, each three minutes long (30 x 3) by BIPOC speakers was created to provide broad foundational skills in verbal and visual communication, using an Equity, Diversity, Inclusion, and Social Justice (EDISJ) lens. A two-day conference offered networking and communication development opportunities to students and early-career scientists in STEM disciplines by connecting them with BIPOC STEM leaders and visionaries who promote STEM advocacy. This paper will discuss the methods used in the creation of the toolkit and conference using an EDISJ lens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.011 | 0.015 |
| Scholarly communication | 0.001 | 0.007 |
| Open science | 0.002 | 0.022 |
| 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 it