Motivate or Demotivate? Factors Influencing Choice of Media as a Career
Bibliographic record
Abstract
The choice of media as a career has conventionally not been a top priority amongst undergraduate students in India. Despite the surging need for responsible media professionals in a developing country like India, this career is not widely accepted or chosen. This research aimed at determining specific motivations among the first-year undergraduate students choosing a career in media. The same were determined through expert interactions followed by an online survey to include over 400 students pursuing an undergraduate programme at various colleges across India. The analysis showed that undergraduate media students are passionate with a deep interest in the concerned field and have an enhanced need to be different from others. They are creative, highly communicative, would like to pursue their interest and passion as well as distinguish themselves from conventional career seekers. Choice of media as a career at the undergraduate level is preferred more by female students compared to their male counterparts. Most interestingly and importantly, media as a career is mostly against the wishes of parents; the influence of parents being negative. This study contributes to a deep understanding of motivational factors and their criticalities in influencing the young generation in India. The factors can aid the educational policymakers, academicians, industry experts, and researchers to develop strategies to encourage students to choose a career in media. This research also serves as a starting point to generate discussions to change the belief and attitudes of parents towards media as a career option for their wards.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".