Bibliographic record
Abstract
As a poet and language educator, I invite and encourage writers to take risks in their writing, to engage innovatively with a wide range of genres, to push boundaries in order to explore creatively how language and discourse are never ossified, but always organic; how language use is integrally and inextricably connected to knowledge, identity, subjectivity, and being in the world. I invite writers, whether English is a first language or an additional language, to know themselves in poetry, to know themselves as poets. We live in a contemporary culture that mostly ignores poetry. This is unfortunate because poetry invites alternative ways of knowing and being and becoming. I encourage all writers to write poetry, because poetry is a capacious genre that opens up endless possibilities for expression and communication. In this essay I offer a series of poems about language, discourse, epistemology, and pedagogy. I hope these poems will invite language educators and scholars from diverse perspectives and experiences to consider how writing poetry stimulates the imagination and inspires the heart to ask questions about our lives and the world we live in.
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.008 | 0.027 |
| Scholarly communication | 0.014 | 0.019 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".