Les concepts souffrent-ils de négligence bénigne en sciences sociales? Eléments d’analyse conceptuelle et examen exploratoire de la littérature francophone à caractère méthodologique
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
Concepts are essential to any scientific endeavour aimed at ‘discovering’ the nature of ‘reality’. Yet, concepts and their analysis have received scant attention from scholars as objects worth studying and teaching in and of themselves, especially in comparison to data collection and analysis techniques. When scholars venture into analyzing concepts, they generally proceed informally, thereby raising serious concerns in terms of the validity of their findings. Conceptual analysis seems to be unrecognized and even unappreciated. This article aims to mitigate this problem. We first offer a few basic principles of conceptual analysis drawn from North American political science. After examining the nature of concepts and their importance to science, the work of Giovanni Sartori is used to establish a few rules and principles to follow when performing conceptual work. Using a sample of francophone methodological literature, we then conduct a plausibility probe of the hypothesis according to which conceptual analysis suffers from ‘benign neglect’. Based on this empirical test, we conclude that while many books explicitly deal with conceptual analysis, very few do so systematically.
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 | 0.036 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.000 | 0.005 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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