Bibliographic record
Abstract
I try to understand the ordeal of solitude by beginning with Marc Augé’s usage on transitional sites as a provocation, which leads us to rethink solitude as a condition of subjectivity and its various inflections, most conventionally as loneliness and, in sociology, as fragmentation, anonymity, alienation, privatization and the various opinions that link it to the deprivation of separation that longs for connection, or, more fundamentally in Simmel, as the ontological view of the tragedy of human limitation. Instead of restricting us to sites, Augé’s provocation suggests that if solitude is one of a family of such usages related to the experience of being alone or apart in such a space, we might then examine ways in which it is oriented to as a condition that can vary according to extremes, say, in the way Arendt and others have contrasted the pain of loneliness with the creativity of solitude. In linking solitude to transitional sites, Augé suggests that there is something about the experience of the in-between, whether of time or space, that illuminates solitude and that makes any relationship to it a potential ordeal. I test the notion by asking how the ordeal pertains to language itself and the intermediacy of a human subject in linguistic space.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.040 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| 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".