Bibliographic record
Abstract
In this article, the author explores the multidimensional nature of relationality in its various complexities, vulnerabilities and possibilities through the lens of experience. By delving into the recollections of the unexpected events of an evening in July, the author ruminates on conditions that promote and hinder interconnectedness in society while also considering the significance of relational ways of knowing and being in present times. The author’s experience is theorized across the disciplines of contemplative inquiry, arts-based research and Indigenous epistemologies. In envisioning pathways forward to foster interconnectedness, a complementary art film is included wherein alternative responses to a ubiquitous question in society, “How are you?”, are offered. Given that interrelationality traverses a range of experience and emotionality, from wonder and joy to sorrow and grief, the article and art film contain sensitive and mature content. Art Film Abstract: This art film is a five-minute breathing snapshot representing the author’s experience on July 10th. Through the modalities of embodied, poetic and performative inquiry, the author offers alternative responses to a ubiquitous question in society, “How are you?”, in the hopes of fostering interconnectedness.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.036 | 0.016 |
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".