Bibliographic record
Abstract
Genetic psychology is dominated by the figure of Piaget, and a philosopher cannot begin to give his comments on the subject without a certain diffidence, as the great man's scathing and uncomplementary remarks about philosophers ring in his ears. So I would like to say something in expiation or extenuation for the lines which follow. The kind of reflection which can be called philosophical cannot simply precede empirical discovery and lay out the field of the possible and the impossible. It can only be a reflection on empirical findings, raising questions about their interpretation, about the connections between them, about the problems they raise or help to solve. In this sense, ‘philosophy’ shades into the kind of reflection and discussion which any innovative empirical scientist must engage in. It can only be distinguished, if at all, in that we like to reserve the term for questions about the more fundamental issues. But wherever one draws the line, I believe that there is a perfectly defensible sense in which one can speak of the philosophical views and ideas of Piaget. And it is in this sense, I believe, that a philosophical reflection on genetic psychology might be useful, even if it loses greatly in value in not being based on the degree and scope of empirical knowledge which searchers in the field have at their disposal. What is genetic psychology? The term might be reserved for a certain field within psychology, that containing all questions to do with ontogenesis.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.034 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".