Political Posters Reveal a Tension in WhatsApp Platform Design: An Analysis of Digital Images From India’s 2019 Elections
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article examines the effects of WhatsApp as a mode of dissemination of political posters. It found that platform affordances that control the crafting and dissemination of political messages open up the possibility of vague political messaging by conforming to the social media’s visual culture and limit the spread of these messages, restricting the ability to organically gather support for a political cause. Despite the growing appeal of social media in political campaigns, social media messages when used by individuals and small, independent social media groups, who are not a part of a larger, organized political party or movement, have little influence on electoral decisions of voters about a political cause that faces weak public support. This was discussed in the context of electoral results of the Leftist political party in India in 2019 national elections. The paper then contributes to our understanding of the extent of the influence of social media platforms on political media messages.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it