Measuring Popularity of Nogoum FM Radio Station among Teenagers in Egypt
Bibliographic record
Abstract
This Paper discusses the amount of popularity Nogoum FM in Egypt as it always claimed to be No 1 ranked Radio station in Egypt by returning to listener’s numbers. To make a good analysis to the future and plans on Nogoum FM the paper investigated the Popularity especially between the young ages (Teenagers) which may have different interests and opinions regarding the radio stations and radio industry as a whole in Egypt. Nogoum FM is the first private radio station since being founded in 2003, and ever since is always said to be the first radio station in terms of listening among people in Egypt after Quran Kareem radio station. What was observed that after the appearance of new radio stations like Mix FM, NRJ and new tech music applications like Anghami and Spotify, Nogoum FM was not on the same solid ground that it was during the previous years despite its efforts to be on track by releasing an application and introducing new generation presenters to give the Radio station the right dosage of youth with balancing its famous presenters, whom it was relied on for a long time. The research studied and took into consideration variables like age, listeners numbers, time and social standard as having major effect on the nowadays popularity of the No1 radio private radio station in Egypt. Tested through questionnaire with sample of targeted age. Literature revealed other variables that had a negative effect on the popularity of Nogoum FM like technology and political stability, yet data collected, and results assured that part of the new variables like Technology effects the new generation, while eliminated other variable like political stability. Finally, paper concluded that Nogoum FM has to give technology the biggest amount of its attention as its most important variable that can affect rest of the variable and will be the main variable for the popularity and the continuity of making Nogoum FM continue to dominate and lead the industry.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".