Relationality as Method: Bridging the Self and Home with the World
Bibliographic record
Abstract
Abstract How do scholars navigate the politics and poetics of relationality in their writing and research? Following a roundtable from the 2024 Annual ISA Convention, this forum explores what is at stake in raising such questions within intellectual work that dissects coloniality and articulates alternative expressions of sociality and connectivity. How do we translate modes of relating that already reflect creative ways of transcending a Manichaeism that can seep into how we talk about relations, coloniality, and politics? What kinds of internal struggles within the field of International Relations render some relational modes recognizable while leaving others absent or peripheral? This forum approaches relationality as both method and ethical orientation for navigating the entanglements of the nation, colonial rule, and imperialism that define the field and our own scholarly practices. Echoing Édouard Glissant, it stages a dialogue on how the powers of relationality play a role in our intellectual pursuits, where a relation is not an absolute to strive for but a totality and a force that is poetic, practical and unceasing—something that continually seeks to be spoken, perfected, and made whole.
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 | 0.033 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.004 | 0.051 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".