MétaCan
Menu
Back to cohort
Record W7023977477

PSYCHOLOGICAL PORTRAIT OF KUZBASS WOMEN ENTERING THE ASSISTED REPRODUCTIVE TECHNOLOGIES PROGRAM

2022· article· en· W7023977477 on OpenAlexaboutno aff

Bibliographic record

VenueMatʹ i ditâ v Kuzbasse · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicSocioeconomic and Demographic Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPortraitMinor (academic)PregnancyQuarter (Canadian coin)Reproductive technologyUnwanted Pregnancy
DOInot available

Abstract

fetched live from OpenAlex

Objective – to study the psychological status of Kuzbass women entering the program of assisted reproductive technologies. Results. The study showed that the level of personal anxiety, as an individual characteristic of women, is higher before entering the protocol, in contrast to the respondents of the control group. The leading motives for pregnancy in this category of women were defined as «Pregnancy to preserve relationships» and «Pregnancy to satisfy the need for love». The motive «Pregnancy as a protest» was not relevant for the Ith group of subjects. 58 % of women before entering the protocol in an emotional attitude to future pregnancy and upcoming motherhood have minor symptoms of anxiety, according to the results of the projective technique. Conclusions. women of Kuzbass, before joining the protocol, are more anxious in personal terms, they have a higher need for love, which they want not only to receive, but also to give. It is important for them to be in a serious and reliable relationship with a man. In an emotional attitude to the upcoming pregnancy and motherhood, most of the subjects have minor symptoms of anxiety, and a quarter of them have a conflict with this condition.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.317
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.014
GPT teacher head0.259
Teacher spread0.246 · 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.

Study designObservational
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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueMatʹ i ditâ v KuzbasseSame topicSocioeconomic and Demographic AnalysisFrench-language works237,207