Bibliographic record
Abstract
When looking through phenomenology articles in human science and philosophy journals, we may be excused to get the impression that they offer an inconsistent array of phenomenology publications. In this article, we describe three simple but helpful distinctions for determining some order: first, the great foundational publications; second, exegetical publications in the wake of the great works; and third, phenomenological studies done directly on phenomena. Our aim in this article is not to lay claim to phenomenology as a label but rather to discuss how "doing phenomenology directly on the phenomena and the things" means taking up a certain attitude and practicing an attentive awareness to the things of the world as we live and experience them. We propose that engaging in philosophical exegesis and argumentation is not very helpful for analyzing and explicating originary meanings of experiential phenomena. And we show how doing phenomenology directly on the things can be facilitated by a phenomenologically inspired interpretive attitude as well as by a sensitive talent for employing phenomenological examples.
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 | 0.161 | 0.168 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.017 | 0.094 |
| Scholarly communication | 0.028 | 0.030 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".