Spaces In-between: Text Poems from Community Practice and Research
Bibliographic record
Abstract
A commitment on the part of the academy to address social issues has increased over the past three decades, resulting in service learning courses, volunteering opportunities, and community-university partnerships. Faculty, staff, and community practitioners collaborating to lead these efforts often carry enormous responsibility and answer to often competing interests of students, community members, and universities. Using the experience of an scholar/artist/teacher in a university-community partnership founded by the first author in a racially polarized town, this article explores the potential of arts-based methods, specifically poetry and collage, to mitigate the consequence of this work. The format is a dialogue between two engaged teacher/researcher/practitioners and friends to clarify the hidden experience of the researcher with narrative truth to articulate and share not only experiences, but also lessons learned as a contribution to our fellow teacher/researcher/practitioners.
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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.021 | 0.034 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".