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Record W7018168727

COVID-19 Pandemisinin Alfa Kuşağı Üzerindeki Etkisine İlişkin Ebeveyn Göürşleri: Tanımlayıcı Çalışma

2022· article· en· W7018168727 on OpenAlexaboutno aff

Bibliographic record

VenueDergiPark (Istanbul University) · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGenerational Differences and Trends
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicQuarter (Canadian coin)Descriptive statisticsSample (material)Sample size determinationGeneration y
DOInot available

Abstract

fetched live from OpenAlex

Objective: The COVID-19 pandemic is a turning point for Generation Alpha. This study was conducted to determine parents’ views of the impact of the COVID-19 pandemic on their Generation Alpha children. Material and Method: This descriptive, comparative, and cross‐sectional study was conducted on 395 parents of Generation Alpha children between January 10 and March 10, 2021. Data were collected using a parent and child sociodemographic form and a questionnaire for generation alpha during the COVID-19 pandemic. Descriptive statistics and paired sample t-test were used for analysis. Effect size was calculated using Cohen's d method. Results: Less than a quarter of the parents stated the negative impact of the COVID-19 pandemic on their children was “fear” (22.8%). Less than half the parents noted that the positive impact of the COVID-19 pandemic on their children was “togetherness” (39.5%). According to parents, their Generation Alpha children spent significantly more time on social media (t = -8.647, p

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.047
GPT teacher head0.287
Teacher spread0.240 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

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