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Record W4392480776 · doi:10.7454/jipk.v24i1.004

Kesiagaan Menghadapi Bencana Pandemi Covid-19 di Kantor Arsip Universitas Indonesia

2022· article· id· W4392480776 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJurnal Ilmu Informasi Perpustakaan dan Kearsipan · 2022
Typearticle
Languageid
FieldBusiness, Management and Accounting
TopicManagement and Optimization Techniques
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)VirologyMedicine

Abstract

fetched live from OpenAlex

The condition of restrictions on community activities due to the COVID-19 pandemic has forced the Archives Office at Universities to adjust archive services. COVID-19 disaster preparedness needs to be implemented within the University of Indonesia Archives Office. This study aims to identify the preparedness of the University of Indonesia Archives Office in dealing with the COVID-19 disaster and. This is qualitative research with case study method. The results show that the University of Indonesia Archives Office has responded to the COVID-19 pandemic situation by carrying out various preparedness efforts that are implemented in service activities and archive management. The obstacle faced by staff and leaders during the pandemic is establishing communication and interaction. Based on the results of the study, the suggestion from this research is that the University of Indonesia Archives Office needs to make a post-disaster recovery plan and look for efforts to establish effective communication during the pandemic between staff and leaders.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.608
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0040.000
Scholarly communication0.0020.005
Open science0.0020.003
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0100.000

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 head0.021
GPT teacher head0.235
Teacher spread0.214 · 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