Communication preferences and social media engagement among Canadian dairy producers
Bibliographic record
Abstract
The objective of this study was to determine communication preferences of dairy producers in Canada. A secondary objective was to evaluate social media engagement of dairy producers. A survey was administered to Canadian dairy producers between March and April, 2015 to collect information on current management practices on their farms. A total of 1,373 Canadian dairy producers responded to the survey, representing a response rate of 12%. The survey consisted of 192 questions; however, only questions regarding producer demographics, importance of information sources, and internet and social media use were evaluated in this study. The primary outcome variables of interest included use of the internet to access dairy information, importance of different sources of information about dairy herd health and management, and use of online search engines and social media platforms. For each outcome, logistic regression analyses were used to investigate associations between the outcome and demographic variables. Veterinarians were viewed as a "very important" source of information by the majority of respondents (79%), whereas milk recording and dairy producer organizations were viewed as a "very important" source of information by 36% of respondents. Other producers (46%) and magazines or newspapers (51%) were commonly viewed as an "important" source of information. Online search engines were commonly used by respondents (94%). Social media was viewed as less important, and had mixed levels of use. YouTube (70%), Facebook (63%), and Twitter (18%) were the most commonly used social media platforms. Eighty percent of Twitter users reported using the platform to interact with and obtain or share information about herd health management online, which was the highest reported interactivy regarding herd health among all social media platforms. This exploratory study offers insight into the communication preferences of Canadian dairy producers and can be used to facilitate future communication strategies aimed at engaging rural farming audiences across Canada.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".