A Triad of Crisis Communication in the United States
Bibliographic record
Abstract
The United States experienced a core-shaking tumble from their pedestal of superpower at the beginning of the 21st century, facing three intertwined crises which revealed a need for change: the financial system collapse, lack of proper healthcare and government turmoil, and growing impatience with the War on Terror. This paper explores the American governments’ and citizens’ use of social network sites (SNS), namely Facebook and YouTube, to conceptualize and debate about national crises, in order to bring about social change, a notion that is synonymous with societal improvement on a national level. Drawing on democratic theories of communication, the public sphere, and emerging scholarship on the Right to Communicate, this study reveals the advantageous nature of SNS for political means: from citizen to citizen, government to citizen, and citizen to government. Furthermore, SNS promote government transparency, and provide citizens with a forum to pose questions to the White House, exchange ideas, and generate goals and strategies necessary for social change. While it remains the government’s responsibility to promote such exchanges, the onus remains with citizens to extend their participation to active engagement outside of SNS if social change is to occur. The Obama Administration’s unique affinity to SNS usage is explored to extrapolate knowledge of SNS in a political context during times of crises.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".