MétaCan
Menu
Back to cohort
Record W2894672723 · doi:10.5539/mas.v12n10p186

The State of Leadership Skills of Senior Students at Schools of 2nd Educational Directory at Zarqa City from Their Point of View

2018· article· en· W2894672723 on OpenAlexvenueno aff
Maram Fuad Abu Al-Nadi

Bibliographic record

VenueModern Applied Science · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDirectoryMedical educationChristian ministryPsychologyStatus quoMathematics educationEducational leadershipPerspective (graphical)PedagogyMedicinePolitical scienceComputer science

Abstract

fetched live from OpenAlex

This study will shed some lights on the state of leadership skills of senior students at schools of 2nd Educational Directory from theirs perspective. The study used descriptive method, and a questionnaire is set up from (20) paragraph. The validity and reliability of study's means were justified. The study case consisted of students in high schools stage at the 2nd directory of education at Zarqa .for the academic year 2017-2018, and a sample of (250) male and female students is taken randomly that the study led to certain findings such as: - The state of leadership skills of senior students at schools of 2nd Educational Directory from theirs perspective. - There were no momentous differences in the estimations of the study's element for status quo of leadership skills that are attributed to variables of specialization, qualification, and gender. The study recommended strengthening the leadership skills of high school pupils by the Educational Ministry and higher education through developing educational and training programs, and they have to cooperate in providing complementary school-university courses in leadership skills.

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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.054
GPT teacher head0.348
Teacher spread0.294 · 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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueModern Applied ScienceSame topicEducation and Islamic StudiesFrench-language works237,207