Bibliographic record
Abstract
The problem of discrimination is relevant for Ukrainian society. According to the results of the study “Human Rights in Ukraine”, conductedby the Democratic Initiatives Foundation. Ilka Kucheriva and the Ukrainian Sociological Service (commissioned by the UN Development Program in Ukraine) state that only a quarter of the population of Ukraine takes itseriously. Based on the analysis of legal documents, scientific literature,we formulate the term “discrimination” as a situation in which a person /people on various grounds (race, skin color, political, religious and otherbeliefs, disability, etc.) is / are restricted in recognition, realization oruse of their rights and freedoms.Discrimination based on disability is defined as eiblism, which characterizesa person by focusing only on his or her disabilities and puts his or her needs to the background in comparison with other people. The author’s experience in teaching and raising a child with hearing disability is described. Ways to ensure the full realization of all human rights and fundamental freedoms by people with disabilities, ways to overcome the eiblism of people with hearing disabilities in society are proposed.
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 | 0.001 |
| Science and technology studies | 0.003 | 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) | 0.000 | 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 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".