The First International Seminar Poltekkes Kemenkes Palangka Raya: A Journey Full of Meaning
Bibliographic record
Abstract
Poltekkes Kemenkes Palangka Raya in collaboration with Indonesian Scholars' Alliance and Global Health Management Journal (GHMJ) successfully held the first international seminar on November 9, 2020. The seminar which took place online in the midst of the raging Coronavirus Disease 2019 (COVID-19) pandemic raised the theme "The New Normal: Creating A Pleasant Virtual Communication”. Five speaker from four countries namely Prof Andrew J. Macnab (Canada), Sr. Merceditas O. Ang, SPC (Philippines), Eva Berthy Tallutondok, M.Sc. (Taiwan), Dr. Yeyentimalla (Poltekkes Kemenkes Palangka Raya, Indonesia), and Prof. Sri Suryawati (Universitas Gadjah Mada, Indonesia) synergizes to convey ideas on how to create fun virtual communication actors. During the pandemic, we do not communicate face-to face, but instead switch to communication using technological devices and chating application. Adequate understanding is needed to be able to communicate with other people virtually where messages are conveyed well and at the same time happy. The journey to the seminar in about four months presents a variety of emotions with negative and positive valences. For example, how to create a seminar participant and photo essays registration website with an inexperienced committee and communication is done virtually. In many ways we argued loudly. This level of difficulty is quite high. Virtual communication is different from face-to-face. We have to be more selective with words because intonation and gesture are absent in communication via WhatsApp and Facebook Messenger. We optimize virtual communication right before we teach it to seminar attendees! This is so much fun! Pandemic may isolate our body, not our ideas. The international seminar was held on Monday, November 9, 2020, to coincide with the 19th anniversary of the founding of the Poltekkes Kemenkes Palangka Raya. In accordance with the health protocol during the COVID-19 pandemic, the online committee from home and from their respective workspaces does not gather in one room. Seminar participants attended the Zoom room after previously registering through the website. At the end of the registration period, 32 photo essays obtained. The details are 16 photo essays from the Department of Nursing, 9 photo essays from the Department of Midwifery, and 7 photo essays from the Department of Nutrition. On November 9, 2020, after the seminar was over, 9 photo essays winners from 9 categories were announced, and been published at the Global Health Management Journal as 2022's Special Edition, following the standard guidelines for Photo Essays.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.018 | 0.013 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.004 | 0.017 |
| Insufficient payload (model declined to judge) | 0.040 | 0.015 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".