Social media: Are the lines between professional and personal use blurring?
Bibliographic record
Abstract
A key aspect of understanding communications in a global environment is understanding social media usage. With the recent dramatic increase in social media usage in the past decade, the incorporation of social media and online platforms into communication strategies of organizations has been intensively discussed and researched. This study investigates social media usage at a global manufacturer to understand how it is being used for business purposes. Are personal and professional lines blurring with social media use? With the increased use of social media in the workplace, our professional and personal lives are increasingly becoming intertwined. The literature suggests that social media interaction and managing the boundaries is more difficult online than offline. Social media is where the lines are blurred between our professional and private lives. It is where we share our food, music, movies, pictures, purchases, politics, and our every-day patterns, alongside our daily professions, on display for the entire world to see. Keywords: social media, strategy, digital, issues, communication, professional
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.007 | 0.037 |
| Scholarly communication | 0.022 | 0.031 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".