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THE PROBLEMS OF GENERATIONALS IN THE DISCOURSE OF THE LIFE SITUATION

2021· article· en· W3170122176 on OpenAlexaboutno aff
L. G. Lebedeva

Bibliographic record

VenuePRIMO ASPECTU · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSociopolitical Dynamics in Russia
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)PopulationLeisure timeSocial issuesAged populationWork (physics)SamaraPsychologySociologyEconomic growthDemographyGeographyMedicineEconomics

Abstract

fetched live from OpenAlex

For successful social policy at different levels of society and the state, an objective assessment of the social situation and its impact on different groups of the population is necessary. In the Samara region, two-thirds of respondents aged 14-30 and 31-45 are primarily concerned about the problem of promising, well-paid work. For half of the respondents aged 46-60, this problem is in the 2nd place in terms of importance. This problem is also of concern to about half of the younger respondents and slightly more than half of the middle-aged respondents - this problem is on the 2nd place in importance for them. For two-thirds of respondents aged 46-60, the problem of limited financial opportunities is on the 1st place in importance. For about a quarter of respondents, the problems of "Getting any job" and "Lack of places where you can spend interesting leisure time" are considered relevant (3rd and 4th places). Thus, for a person, even in difficult socio-economic conditions, the problem of leisure is also important. Among the most notable (on the 5th place) is the problem of obtaining higher education, which is most relevant for young people. All problems (and not only those that have taken leading positions in opinion polls) require attention to themselves, taking into account the age characteristics and special needs of people of different generations.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.277

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.346
Teacher spread0.315 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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Same venuePRIMO ASPECTUSame topicSociopolitical Dynamics in RussiaFrench-language works237,207