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Record W2950900555 · doi:10.21831/jk.v3i1.16189

UNIVERSITY GOVERNANCE THROUGH WEBSITE DISCLOSURE

2020· article· en· W2950900555 on OpenAlexaff
Amelia Setiawan, Chatherine Melinda, Gery Lusanjaya, Damajanti Tanumihardja

Bibliographic record

VenueJurnal Kependidikan Penelitian Inovasi Pembelajaran · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBig Data and Business Intelligence
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsNonprobability samplingAccreditationLibrary scienceBusinessPolitical scienceSociologyComputer scienceLaw

Abstract

fetched live from OpenAlex

This study was aimed at identifying university’s disclosure about their management through their websites. Completeness of information in this report should be made to improve transparency of information. This study was conducted through observation on the website and data collection on relevant regulations and literature studies to support this research. This study used 50 universities as samples. The sample selection used was purposive sampling method. The ten domains studied included identity, tridharma, governance, academics, public recognition, actuality, accessibility, stakeholders, internal facilities, and external facilities. The results show that the university website from Java region disclose more adequate than outside Java. While based on accreditation, universities with “A” accreditation disclose more adequate compared to “B” accreditation. Based on the type, State Universities disclose more adequate than private universities. Conclusions of this study, there are many universities that do not fully disclose the information on their website. And this should be a concern for every university and regulator.Transparansi Pengelolaan PERGURUAN TINGGI melalui Penyajian Informasi pada Situs webPenelitian ini bertujuan untuk mengamati transparansi perguruan tinggi (PT) mengenai pengelolaan operasinya melalui situs web. Kelengkapan informasi pelaporan ini perlu diperhatikan untuk meningkatkan transparansi informasi. Penelitian deskriptif dilakukan melalui observasi pada situs web dan pengumpulan data atas regulasi yang relevan serta studi literatur untuk mendukung penelitian. Penelitian ini menggunakan 50 PT sebagai sampel. Pemilihan sampel menggunakan purposive sampling method. Sepuluh domain yang diteliti mencakup identitas, tridharma, tata kelola, akademik, pengakuan publik, aktualitas, aksesibilitas, stakeholders, fasilitas internal, dan fasilitas eksternal. Hasil penelitian menunjukkan bahwa situs web Perguruan Tinggi yang berasal dari wilayah Jawa mengungkapkan lebih memadai dibandingkan dengan wilayah di luar Jawa. Adapun berdasarkan akreditasi, Perguruan Tinggi yang memiliki akreditasi “A” mengungkapkan lebih memadai dibandingkan dengan yang memiliki akreditasi “B”. Berdasarkan jenisnya Perguruan Tinggi negeri memiliki kelengkapan informasi lebih memadai dibandingkan Perguruan Tinggi swasta. Kesimpulan penelitian ini, masih terdapat banyak Perguruan Tinggi yang tidak mengungkapan secara lengkap informasi pada situs web, dan semestinya menjadi perhatian bagi setiap Perguruan Tinggi dan juga regulator.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.717
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.004
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.004

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 head0.062
GPT teacher head0.247
Teacher spread0.185 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations1
Published2020
Admission routes1
Has abstractyes

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