Building Representative Community Archives: Inclusive Strategies in Practice
Bibliographic record
Abstract
In 2017, the Watzek Library Special Collections began the work of building relationships with the Vietnamese community in Portland, Oregon to address a historical gap in the records housed in their collections. Renowned for its extensive collection of books related to the Lewis and Clark expedition, it became apparent to the Special Collections team that the collection did not fully represent Portland’s history or diverse population (39). Thus began a nearly decade-long project led by Hannah Leah Crummé, the current Head of Watzek Library Special Collections, alongside Dr E.J. Carter, Zoë Maughan, and Vân Truong, to document the experiences of Vietnamese immigrants and refugees whose presence in Oregon has been steadily growing since the 1970s (40).
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.
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 | 0.119 | 0.111 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.045 | 0.032 |
| Scholarly communication | 0.041 | 0.043 |
| Open science | 0.010 | 0.072 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.026 | 0.007 |
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".