Posthumanisms beyond Disciplines
Bibliographic record
Abstract
Posthumanism and its core ideas have been spreading in different parts of the world and in various areas of human interest as a response to the multi-faceted problems human and more-than-human worlds are facing. In the spirit of addressing the burning questions of our times from diverse global and multi-disciplinary perspectives within the context of Posthumanism, we came together to start a new journal: Journal of Posthumanism (JoPH). As the field’s first multidisciplinary and multilingual journal, the JoPH, aims to bring together conversations that go beyond Anglo-American academia, including marginalized ontologies, epistemologies, methodologies, and axiologies, as well as underrepresented disciplines, experiences, views, cultures, and histories. By marking global multiple chapters and discussions in the area, the JoPH promises to expand fresh and diverse understandings of posthumanisms. With the hope of continuing the dialogue on a global forum in solidarity with other journals, we invite all researchers, writers, artists, activists, and scholars from different disciplines to share their work with us.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.061 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 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".