Diversity by design: From concept to action
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
ABSTRACT Last year, in a guest editorial for the Library Quarterly (LQ) we proposed the concept of diversity by design (DbD) and posited it as a concept relevant to workplace environments, community engagements and graduate LIS education. We invited LQ readers “to contemplate whether this concept ma[de] sense to them and, if yes, how it work[ed] in their respective” situations [1: 88]. We brought to light “the multiplicity of contexts that give diversity meaning and life in our complex field” [ibid] and demonstrated that it was integral, rather than superfluous, to our field and way of being. Finally, we gave examples of how “discounting or underappreciating” diversity “may have a disintegrating effect on our practice, scholarship, and education” [ibid]. This poster will introduce the concept of DbD; provide examples of several case studies which show the difference between “diversity as a bonus” and “diversity by design”; and include feedback and insight from the DbD grant‐funded international symposium in Toronto, Canada, in September 2017.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.000 | 0.008 |
| 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 it