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Record W4411396877 · doi:10.53762/yerfxj31

10.53762/yerfxj31

2000· article· en· W4411396877 on OpenAlexvenueno aff
Asif Minhas, M. Zeeshan Gul

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsEmotional competencePsychologyCoping (psychology)PerceptionCompetence (human resources)Emotional stressApplied psychologyDevelopmental psychologyPopulationEmotional regulationStress managementSocial psychologyEmotional intelligenceClinical psychologyMedicine

Abstract

fetched live from OpenAlex

This study examines the domains of emotional stability among 153 school heads in five southern districts of KP, focusing on emotional awareness, emotional regulation, emotional expressivity, social competence, and stress coping. A researcher-made questionnaire was used to assess their perception levels for the above-mentioned domains of emotional stability. The questionnaire was properly validated and its reliability was recorded as 0.82. The population of the study comprised 572 school heads. The questionnaire was distributed among 235 school heads among which 153 responded properly. Most school heads (64%) responded to the high impact of stress-coping skills on their work performance. The lowest impact domain was considered emotional awareness (39%). These results highlight the need for training programs and skill development practices to enhance stress-coping capabilities in school heads. Moreover, encouraging discussion forums for emotional awareness among school heads, and creating a supportive environment for expression, feedback, and emotion management is highly recommended.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.060
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.9400.935

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 head0.020
GPT teacher head0.269
Teacher spread0.249 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2000
Admission routes1
Has abstractyes

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