Conceptual Engineering Methodological and Metaphilosophical Issues
Bibliographic record
Abstract
Conceptual Engineering (CE) is a dynamically developing field of (especially analytic) philosophy. It aims at evaluating, reanalyzing, and redefining concepts as well as their relations with the world and language. Work in CE is of considerable interest not only for philosophers, but also linguists and researchers within ethics, social sciences, and AI. The chapters included in this volume are concerned with the most important and challenging methodological and metaphilosophical aspects of CE. The authors, representing universities and research centers from Portugal, Germany, the Netherlands, United Kingdom, Canada, Norway, Japan, and Poland, deal with concept development and dynamics, terminological disputes and negotiation, different aspects of conceptual ethics, digital humanities and explainable AI, and concept development in social sciences. The volume shows the increasing importance of CE, both as a field within philosophy, and also as a philosophical method
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How this classification was reachedexpand
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".