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Record W4281568515 · doi:10.5539/hes.v12n2p193

Employability and Job Performance of Graduates of Occidental Mindoro State College Graduate School

2022· article· en· W4281568515 on OpenAlexvenueno aff
Venessa S. Casanova, Wenceslao M. Paguia

Bibliographic record

VenueHigher Education Studies · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHuman Resource and Talent Management
Canadian institutionsnot available
Fundersnot available
KeywordsGraduation (instrument)EmployabilityPromotion (chess)Medical educationPsychologyUnit (ring theory)MedicinePedagogyEngineeringMathematics educationPolitical science

Abstract

fetched live from OpenAlex

This descriptive study determined the employability and job performance of Occidental Mindoro State College (OMSC) Graduate School graduates. The study was conducted from January 2020 to August 2020 at OMSC Main Campus, San Jose, Occidental Mindoro, Philippines. A total of 40 respondents selected through simple random sampling participated in the study. A self-made questionnaire was the main instrument used in gathering data for the endeavor. Data were analyzed using frequency and percentage, weighted mean, and Pearson-r moment correlation. Most respondents are middle-aged females who took Master of Arts in Education and graduated in 2013. The majority of the respondents are regular employees designated as unit heads, recently promoted, attended a few seminars and training, and did not receive any award and recognition after obtaining their master's degree. On the other hand, the respondents perform their jobs very well, as shown in their work quality, work habits, human relations, and leadership skills. Furthermore, there is a relationship between gender, graduation year, academic program, promotion, and graduates' job performance. It was concluded that gender, graduation year, academic program, and promotion might affect the graduates' job performance.

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)0.000
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 score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.055
GPT teacher head0.291
Teacher spread0.236 · 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

Citations10
Published2022
Admission routes1
Has abstractyes

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