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Record W3045424673 · doi:10.5539/ies.v13n8p88

Social Variables and Dropout Tendencies among Secondary School Students in Ikom Education Zone, Cross River State, Nigeria

2020· article· en· W3045424673 on OpenAlexvenueno aff
Joy N. Njoku, Edna A. Osang, Blessing Agbo Ntamu

Bibliographic record

VenueInternational Education Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Substance Use and School Attendance
Canadian institutionsnot available
Fundersnot available
KeywordsDropout (neural networks)PsychologyData collectionPopulationTest (biology)Mathematics educationSocial psychologyDevelopmental psychologyDemographySociologySocial science

Abstract

fetched live from OpenAlex

This study was on social variables and dropout tendencies among secondary school students in Ikom education zone, Cross River State, Nigeria. The social variables considered were substance abuse, family type and teacher/students relationship. Out of population of 7228 students, sample of 506 students were randomly selected for the study. A survey design was adopted. The instrument used for data collection was questionnaires titled ‘Social Variables and Dropout Tendencies Questionnaire’. Three hypotheses were formulated and tested at .05 level of significant. The statistical tools used are Pearson Product Moment Correlation Coefficient and Independent t-test. The results showed that there was significant relationship between (i) substance abuse and dropout tendencies. (ii) family type and dropout tendencies (iii) teacher/student relationship and dropout tendencies. The results were discussed and the researchers recommended that: (i) students be monitored and counseled against substance abuse both at home and in school. (ii) parents should for the sake of their children stay together and train them. (iii) teachers should create conducive and favourable environment for the students to learn.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.018
Threshold uncertainty score0.654

Codex and Gemma teacher scores by category

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

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 head0.040
GPT teacher head0.410
Teacher spread0.370 · 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 teacher head, 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

Citations7
Published2020
Admission routes1
Has abstractyes

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