Bibliographic record
Abstract
Zygmunt Rewkowski received the Vilnius University’s Chair of the Probabilistic Theory – established specially for him – when he was only twenty two. Unfortunately, two years later, in the repressions following the November Uprising, the czar of Russia dissolved the University, and after the following two years the tsarist authorities exiled the young academic for twenty-fi ve years of military service in the Caucasus. After serving the punishment, he worked as a communications engineer for the next quarter of a century. During that period, i.e. at the end of the nineteen sixties, he undertook independent research in the fi eld of Economics. Using the tools of Mathematics he created a general theory of works which aimed at designating a minimum price and the optimum time of work. Z. Rewkowski, as the fi rst of Polish economists, applied differential calculus for this designation. By insisting on the creation of conditions for good work, he became a forerunner of Praxeology to be co-created several decades later by Tadeusz Kotarbiński. In addition to the mathematic and economic works he also published a statistical treatise devoted to the average, and the method of the sum of squares of errors. The average were used to estimate the parameters of the general price equation which form part of his theory of works. In this way he joined the group of forerunners of Econometrics. In the nineties he applied statistical methods to medical research. Despite all this, he remained unknown as a theoretician of Statistics and forgotten as a theoretician of Economics.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
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".