A RADIO ANNOUNCER: STRESS LEVEL & PERFORMANCE IMPACT ON RETAILERS INTENTION TO ADVERTISE
Bibliographic record
Abstract
The stress level on Indonesia radio announcer has reach 50,30% for past two years. Their obligations \nto connect with wider public are indeed challenge even though it is only known by its voice. In addition, this \nprofession also requires caution with words that are issued when on air. What's more, the radio broadcasting \nprofession in Indonesia ranks sixth out of the 9 most stressful jobs in years 2015. The Indonesian National Private \nBroadcast Radio Association (PRSSNI) state advertising expenditure on radio (Radex) reaching 1.2 trillion IDR \nuntil the end of the third quarter of year 2017. The portion of radex relatively lower compared another media; \notherwise advertising is the biggest revenue for radio. This examination plans to test the effect of radio broadcaster \nwork anxiety on the intention to promote moderate by performance, 50 samples taken with simple random sampling \nfrom consumer in city of Bandung, Indonesia that advertise on radio x. Partial Least Square Square (PLS) utilized \nfor data investigation, the results shown performance play important role in rising or lower impact of work stress \nlevel on intention to advertise, this mean performance proven as moderating variable and work stress level impact \npositively on intention to advertise.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".