Bibliographic record
Abstract
Scientific views on the processes of constructing ethnocultural self-identification in culturological discourse are researched and systematized. The concept of "ethnocultural self-identification" is specified, the basic conceptual approaches to research of ethnocultural self-identification are considered and analyzed. It is revealed that ethnocultural self-identification is determined by a complex set of factors: historical, social, economic, political, psychological and cultural. In modern culturological discourse, ethnocultural self-identification is seen mainly as the search for and discovery of traditional values in the context of everyday space. Despite the differences in the modern scientific dimension of approaches to the problem of ethnocultural self-identification, most researchers agree that this phenomenon is a complex process of identification with a particular ethnocultural group, assimilation of personality to a particular image, which occurs as an individual part of it and experiencing one's own devotion to it, not autonomously, but together with other processes of human activity (social, labor, political), in the process of communication and the context of everyday behavior. Constantly comparing their own actions and deeds with the norms and patterns of a particular ethnocultural group, the individual positions them as standards, criteria of behavior, self-reflection.The author concludes that ethnocultural self-identification is one of the most important human values, because fixing the unity of individual interests with the interests of its ethnic community ensures self-preservation as a person and as an individual, contributes to the needs of self-affirmation and self-expression
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 | 0.019 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.010 | 0.056 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".