Information Seeking Behavior and Utilization of Social Media for Agricultural Information by Farmers of Prayagraj District of Uttar Pradesh
Bibliographic record
Abstract
Social media is becoming very important implement in agriculture to edge people to people due to its capacity to connect with farmers and agribusiness people around the globe over hug geographical distances. At present time there are 2.078 billion social media user in the world. The study was conducting in purposely selected Prayagraj district of Uttar Pradesh of also purposely two selecting blocks two villages from each block. Selected for the study Thus, in all, four villages thirty farmers were selected randomly. Thus, total 120 respondents were selected randomly and interviewed with the help of well semi structured schedule. The statistical tools/technique was used to computing the data and information. Descriptive research design was followed for the analysis. Maximum number respondents communicate through social media and WhatsApp is highly exposed and adopted by the respondents in the study area. Smart phones, computer usage and internet should be promoted among stakeholders (esp. farmers).majority of the respondents information getting through Kisan SMS Portal. The highest utilization level of the respondents about social media programme was WhatsApp with a weighted mean score of 1.58 and it was ranked first, followed by the Kisan SMS Portal a weighted mean score was 1.43 with ranked was second, while YouTube was ranked third and so on.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.005 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".