Bibliographic record
Abstract
Researchers need to stand amidst traumatized people to learn from them to begin to understand the meaning of their suffering. Distance is lessened and listening intensified as researchers ask the question of what it means to suffer. Through this paper, we explore as compassionate researchers, the meaning of suffering, its language and consequence with the intention to understand, inform, enlighten and challenge ourselves to learn from each other. We offer a perspective for human science research created through a hermeneutic consciousness about suffering where understanding takes its form analytically as an interpretation, of an interpretation. This unquiet understanding, a chaotic bricolage of suffering was brought together hermeneutically to unify a diversity of suffering narratives within the context of honoring personal narratives, while confronting the challenges of academic writing. “I do not think realizing that we who [suffer] are utterly lost and broken, necessarily causes despair. What breaks us is the impression that everyone else isn't”. Our work as researchers, writers and teachers then becomes bringing the meaning of suffering into language and understanding what challenges us to confront and humanize research beyond academic expectations of “…clean and reasonable scholarship about messy, unreasonable experiences”. The hermeneutics of suffering prevents personal narratives from becoming “an exercise in alienation”, but rather as an invitation for humanizing conversations about suffering, where their unique qualities and characteristics are brought back interpretively into the world. We belong to our suffering; it humanizes all worldly activities through a common ‘rough-ground’ from which we can become more compassionate, generous and open to the experiences of others. A committed engagement between the researcher and the people who suffer, together becoming experienced about the many faces of suffering, deconstructing its complexity and thus co-creating a deeper understanding how to communicate, respond, share language, and learn from each other.
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 | 0.029 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.018 | 0.139 |
| Scholarly communication | 0.019 | 0.035 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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".