Autopraxeography: a method to step back from vulnerability
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose Studies on vulnerability in the workplace, although relevant, are rare because it is difficult to access. This article aims to focus on the benefits of using autopraxeography to study and step back from vulnerability at work. Design/methodology/approach Autopraxeography uses researchers' experience to build knowledge. Findings Autopraxeography provides a better understanding of vulnerability and the opportunity to step back from the difficulties experienced. Instead of ignoring experiences related to vulnerability, this method makes it possible to transform them into new avenues of knowledge. Moreover, it enables researchers to step back from experiences of vulnerability, thus making them feel more secure. Originality/value The main differences from other self-studies stem from the epistemological paradigm in which this method is anchored: pragmatic constructivism. The most important difference is the production of generic knowledge in three recursive steps: writing in a naïve way, developing the epistemic work and building generic knowledge.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 it