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Record W4285316842 · doi:10.24114/icp.v2i1.31158

PENGARUH IKIGAI GURU BK DAN IKLIM KERJA GURU BK DI SEKOLAH TERHADAP KINERJA GURU BK

2021· article· en· W4285316842 on OpenAlexaff
Leni Murni Hayati, Firman Firman, A Muri Yusuf

Bibliographic record

VenueIndonesian Counseling and Psychology · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSchool Leadership and Teacher Performance
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsPsychologyPopulationPedagogyMathematics educationSociologyDemography

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the effect of Counselor Ikigai and the Teacher Counseling's work climate on the performance of Teacher Counselings. This type of research used a descriptive method with a quantitative approach. This study also uses the regression method which aims to examine the effect/value of the influence of two independent variables on one dependent variable. The research population is all Teacher Counselings in South Solok Regency. A sample of 39 respondents was Teacher Counselings. The results of data analysis and hypothesis testing indicate that the three hypotheses tested in this study are acceptable. The results show that Ikigai and work climate together can explain the performance of Teacher Counselings at SMA Solok Selatan Regency

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.046
GPT teacher head0.346
Teacher spread0.300 · 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 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
Published2021
Admission routes1
Has abstractyes

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