The Community Needs to Research Problem Development in Areas Under the Responsibility of Suan Sunandha Rajabhat University
Bibliographic record
Abstract
This study aimed to investigate the community needs in the areas under the responsibility of Suan Sunandha Rajabhat University in order to propose the research problem. Regarding research procedures, the qualitative research method was initially employed to collect data, and the data was consequently analyzed to create the research problem to examine the communities. The scopes of this study were separated into three parts comprising: firstly, the scope of areas under the responsibility of Suan Sunandha Rajabhat University consisted of 1) Dusit – Phranakhon in Bangkok, 2) Khlong Yong in Nakhon Pathom, 3) Sarapee, Bangkontee in Samut Songkhram, 4) Ban Muang - Ban Wang Thong, Kham Chanod in Udon Thani and 5) Ngao, Muang Ranong in Ranong. Secondly, the scope of contents was used to investigate community needs in the area under the responsibility of Suan Sunandha Rajabhat University. Lastly, the scope of samples employed the simple random sampling by drawing lots technique in specifying the samples. The samples were classified into 3 major groups including 100 farmers, 100 SME entrepreneurs, 100 OTOP entrepreneurs as well as 30 government officials. according to the research instruments, the interview form and questionnaire which their questions based on the conceptual framework were used in the in-depth interview as well as participant observation to gather information about community needs. Furthermore, the focus group discussion was also applied into collecting data in the five areas under the responsibility of Suan Sunandha Rajabhat University. The results elucidated that the problems which the researcher could further utilize in creating the research problem involved with economy, environment, education as well as health. In each area, there was a variety of needs on different context. For instance, the community needs to research problem development in the areas of Sarapee village, Bangkontee district in Samut Songkhram, Khlong Yong district in Nakhon Pathom and Ngao sub-district, Muang Ranong district in Ranong related to agricultural-product processing due to the fact that these areas mainly produced a large number of agricultural products. In addition, the needs toward health in all areas were consistent (e.g., promoting the community to have better knowledge about disease prevention as well as health care).
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".