The Conditions of Consensus: Discipline and Governmentality in Humanitarian Communication
Bibliographic record
Abstract
This study engages and builds on the work of those who have examined the prevailing truths that shape humanitarianism and make it appear rational within an inequitable world. Specifically, the study examines how the Canadian Red Cross’s communication practices portray the world’s poorest aid beneficiaries and their potential donors, including their relationship and the world in which they live. The analysis draws on Foucault’s mid-to-late works concerning discipline, governmentality, and biopolitics to examine how truth and subjectivity work together in the context of humanitarian communication. The data are drawn from the Canadian Red Cross (CRC) website, which is the CRC’s primary medium of communication to Canadians. The website’s practices of representation are examined for how they organize a regime of truth and set up the conditions of consensus concerning the relationship between the wealthy and the poor. The study argues that the CRC website’s practices of representation produce aid subjects as problematic, life-threatened bodies that must be trained to become resilient in order to survive a disastrous world. When viewed within an increasingly market-centered global environment, this life-protecting and resiliency-building message can be seen to maintain the consensual conditions in which both the poorest and the wealthy seek not to change the world, but rather only ensure their own survival within it. The message’s cost is that it leads both wealthy and poor away from developing themselves and each other as politically-conscious citizens. The study demonstrates how the construction of subjectivity is a key mechanism in the maintenance of prevailing truths that sustain the wealthy world at the expense of the poor. In addition, the study contributes to the literature by providing a Foucaultian method for analyzing organizational communication texts and websites.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".