Bibliographic record
Abstract
A media ethics of the future needs to be ecumenical, open, and global. This chapter explores the third feature, a global ethics for news media. It argues that media ethics needs to take a global approach to responsible journalism. Its aims, principles, and practices have to be altered to reflect the global nature of media. The emergence of multi-media communication is not unrelated to the rise of global news media. The same technology that allows media to be interactive across multiple platforms – satellites, digital computers, the Internet – allows media to be global in scope. The three features cited above are inseparable in reality. However, for purposes of analysis, we focus in this chapter on the theoretical and practical impact on ethics of the globalization of media. The discussion begins by explaining why media ethics needs to “go global” and what is meant by global media ethics. Then, I argue that the best philosophical basis for a global ethics, in general and in media, is cosmopolitanism. I show how cosmopolitanism reinterprets the media’s aims and principles in terms of promoting a global human good. Cosmopolitanism would change how global events are covered and would alter how journalists think about patriotism. The chapter concludes by discussing how ethicists, citizens, and journalists can build a global media ethics, theoretically and practically.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.015 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".