Humanitarian Communication Through the Lens of Feminist Ethics of Care
Bibliographic record
Abstract
Ethics are the driving force of the humanitarian field, a domain that has been governed by general and universal ethical principles. Researchers have largely focused on studying the organizational commitment to these principles, paying less attention to the role-specific ethics of this field. Moreover, researchers who consider the humanitarian field from a media studies lens have often focused on media representation, while questions about communication as practice are sidelined. In this paper, I approach humanitarian ethics with a particular focus on role morality and communication practices. With a particular focus on the role of a humanitarian communications specialist, I argue, in this paper, that the feminist ethics of care is a useful ethical framework that can guide communication specialists to better practices when they are in the field of operation. I also answer the following research questions: What are the main ethical principles that humanitarian communication specialists are expected to observe as humanitarians? Why are these principles insufficient? How might feminist ethics of care fill the gap left by current humanitarian principles and what would be the added value of this framework for practicing humanitarian communication? To answer, I ground my approach in an experiential understanding built from my personal experience as a humanitarian communications specialist. Second, I offer a literature review to highlight the common ground between humanitarian ethics and the feminist ethics of care and the added value of the feminist ethics of care why applied by humanitarian communication specialists. Third, I provide some examples of communications practices that may follow the feminist ethics of care model.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.054 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".