Bibliographic record
Abstract
ÄlĂĄnek poukazuje na problĂŠm, do jakĂŠ mĂry je smysluplnĂŠ rozliĹĄovat pĹĂrodnĂ vÄdy, sociĂĄlnĂ vÄdy a humanitnĂ vÄdy, respektive co majĂ tyto vÄdy spoleÄnĂŠho potud, pokud je lze skuteÄnÄ nazĂ˝vat vÄdou. Jde o nĂĄsledujĂcĂ otĂĄzky: JakĂ˝ je rozdĂl mezi humanitnĂmi a sociĂĄlnĂmi vÄdami? Je moĹžnĂŠ vĂŠst ostrou demarkaÄnĂ linii mezi humanitnĂmi a pĹĂrodnĂmi vÄdami a jejich metodami? Co vlastnÄ opravĹuje dotyÄnĂ˝ systĂŠm vĂ˝povÄdĂ k tomu nazĂ˝vat se vÄdou? Je osudem humanitnĂch vÄd "kvantitativnĂ smrt" Äi je naopak moĹžnĂŠ vedle hi-tech ĂşspÄĹĄnĂ˝ch exaktnĂch vÄd povaĹžovat humanitnĂ vÄdy za nepostradatelnĂŠ know-how pro pĹeĹžitĂ lidskĂŠ spoleÄnosti? OdpovÄdi na tyto otĂĄzky se budou opĂrat o definici sociĂĄlnĂ vÄdy Maxe Webera, poĹžadavek autonomie metod humanitnĂch vÄd klasickĂŠ hermeneutiky, univerzĂĄlnĂ hermeneutiku Hans-Georga Gadamera, scientistickĂ˝ nĂĄvrh novopozitivismu a v neposlednĂ ĹadÄ o ĹeĹĄenĂ problĂŠmu hodnotovĂŠ neutrality vÄdy Hanse Alberta.
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 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 | 0.001 | 0.000 |
| 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 | 0.002 |
| 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 | 0.001 |
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 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".