Bibliographic record
Abstract
The creation of visually diverse media content is significant in the context of Maldivian media landscape. This research aims to explore how it is possible to enhance the representation of Maldivian narratives and the connection to the local audience in the media content. Previous studies have found cultural and linguistic diversity, gender equality in newsrooms and the audiences’ interest in local news (Friedland et al., 2012) but there is a research gap that presents a framework for implementing these objectives. The need to develop a sustainable and open media environment for citizen journalists and creatives to produce meaningful and socially relevant content is the motivation for this research. To address the research questions of this study, data was collected using a mixed method through surveys to understand public opinion and the current state of media in the Maldives. The results indicate that local content is highly valued and that financial assistance for media practitioners is needed. Moreover, the research suggests the need to monitor and assess the quality of content, willingness to pay for quality content, ensure media freedom, and engage with the vulnerable groups. The implication of these findings also support the idea that the media industry has to embrace disability as an investment on the future workforce and active audience to gain its credibility.
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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 | 0.015 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.009 | 0.020 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.005 | 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".