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Record W2884593471 · doi:10.31795/baunsobed.437734

İŞE YABANCILAŞMANIN SANAL KAYTARMA ÜZERİNDEKİ ETKİSİ

2018· article· tr· W2884593471 on OpenAlexaff
Mustafa Babadağ

Bibliographic record

VenueBalıkesir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi · 2018
Typearticle
Languagetr
FieldSocial Sciences
TopicCyberloafing and Workplace Behavior
Canadian institutionsBell (Canada)
Fundersnot available
KeywordsPsychologyHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Bu araştırmanın amacı, işe yabancılaşmanın sanal kaytarma davranışı üzerindeki etkisini araştırmaktır. Araştırmada bir belediyede masa başında memur olarak çalışan 187 çalışandan anket tekniği ile veri toplanmış ve verilerin analizleri SPSS ve AMOS programıyla gerçekleştirilmiştir. Araştırmada ilk olarak kavramsal bir çerçeve çizilmiş; kuramsal bilgilere ve daha önceki görgül araştırmaların sonuçlarına bağlı olarak değişkenler arasındaki ilişkiler belirlenmiş ve hipotezler geliştirilmiştir. Daha sonra, anket ile ulaşılan veriler analiz edilmiş ve bulgular yorumlanmıştır. Bu kapsamda da araştırmacılara ve örgütlere önerilerde bulunulmuştur. Verilerin analizinde Açıklayıcı Faktör Analizi, Doğrulayıcı Faktör Analizi, Korelasyon Analizi ve Regresyon Analizi kullanılmıştır. Analizler sonucunda ulaşılan bulgulara göre, işe yabancılaşmanın sanal kaytarmayı ve sanal kaytarmanın alt boyutlarını (önemli sanal kaytarma ve ciddi sanal kaytarma) pozitif yönde ve anlamlı olarak etkilediği belirlenmiştir.

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0290.007

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 head0.026
GPT teacher head0.287
Teacher spread0.261 · 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 designNot applicable
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

Citations17
Published2018
Admission routes1
Has abstractyes

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Same venueBalıkesir Üniversitesi Sosyal Bilimler Enstitüsü DergisiSame topicCyberloafing and Workplace BehaviorFrench-language works237,207