Mermaid (A/Be)musings From/on/Into/Through the In-Between
Bibliographic record
Abstract
In this article, we take a retrospective look at a prior collaboration that involved the process of making art together, dialogue, and sharing stories of experience. More specifically, we share with you some of the storied text fragments that were elicited when we looked again, and together, at our very first co-created hybrid image. By putting forward our cultural storied texts, we—two women academics who identify with the experience of being an immigrant—wish to contribute to ongoing discussions on the value of fostering the cultural imagination through artful community-based approaches that invite the creation of our images and incite the telling of our stories, in our own voices. As well, we hope to illustrate how the stories that surfaced from/on/into/through our re-engagement with our co-created image of a mermaid helped us come to deeper understandings of our cultural hybridity, characterized primarily by living, learning, and knowing in spaces of in-betweenness.
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 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 | 0.002 | 0.057 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".