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Record W3094227494 · doi:10.20961/shes.v3i1.45060

Community Empowerment in Facing Covid-19 Disaster by KKN Students Of Universitas Sebelas Maret in Wonosobo District

2020· article· en· W3094227494 on OpenAlexaff
Chatarina Muryani, Fransisca Trisnani Ardikha Putri, Puji Lestari, Rahendhiki Ratik Galindra, Ainaya Nurrachma Hakim, Almara Yoyok Arighynata, Danang Mika Daya, Dika Ulfatus Sa'adah, Rima Rianti, Dwitama Alphin Usdianto, Lulu Febriana Damayanti

Bibliographic record

VenueSocial Humanities and Educational Studies (SHEs) Conference Series · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCOVID-19 Prevention and Impact
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)EmpowermentPandemicSociologyPolitical scienceMedicine

Abstract

fetched live from OpenAlex

<p><em>Sebelas Maret University Real Work Lecture (KKN) during the COVID-19 pandemic was still carried out with a focus on problems that occurred during the COVID-19 pandemic. The location for the Covid-19 KKN placement is also specifically in the Neighborhood (RT) where the KKN students live. In the Wonosobo Regency area there are 10 Sebelas Maret University students who are undergoing KKN, they are members of the Group 170 UNS Covid-19 Batch-2 KKN.These students have successfully carried out community empowerment activities in the form of (1) Socialization to the community about COVID-19 and food security, (2) Training and practices related to family resilience in the face of the COVID-19 pandemic, including training and practice of making masks, making hand sanitizers, planting vegetables in hydroponics and planting in pots and family waste. Based on the family resilience survey that has been carried out, as many as 70% of the respondent's families are in the high family toughness category.</em></p>

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
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
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.182
GPT teacher head0.415
Teacher spread0.233 · 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.

Study designQualitative
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
Published2020
Admission routes1
Has abstractyes

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