The Creators of Oikophobia: To Methodology of Research of Domestic Space Demonization as Pragmatic Mass Media Effect
Bibliographic record
Abstract
On the basis of theoretical analysis of sociological, cultural, psychological, medical, demographic and psycho physiological scientific sources, the author defines the methodological basis of research and quantification of mystical fear as a factor of housing prejudices, preferences and attitudes of the population, as a component of housing deprivation, which occurs as a result of demonization of the house and the formation of magical stigma in mass culture. Modern Russian sociology pays little attention to �mystical�, �supernatural� component of relationships between Man and Space, but the theme is legitimized by W.L. Warner, by E. Goffman's concept of "involvement". This concept removes the question of the scope of the supernatural faith in a secular society as supposedly mandatory for susceptibility to magical stigma. This is confirmed by some empirical sociological and anthropological studies of housing prejudices in UK, Canada and Russia (P. Cowdell, D. Kelso, I.V. Utekhin). Having identified the key components of the process of demonization of home space by means of mass media, we find the probable points of its intersection with the processes of stratification in the housing sector. Suburbanisation and �privatization� as a part of suburbanism as a way of life, living in historic buildings as well as in communal apartments are the types of living conditions that create the frame most suitable for the "context-induced" experience of external evil invading personal space, especially against the background of high viewer involvement in horror films watching.
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".