Electoral Games, Frames, and Ethnic Party Moderation: The Limited and Selective Moderation of the Bharatiya Janata Party
Bibliographic record
Abstract
This dissertation seeks to explain how and why ethnic parties like the Hindu nationalist party in India, the Bharatiya Janata Party (BJP), moderate in the electoral arena while also examining the constraints on their electoral moderation. Questioning the restricted range of outcomes offered in extant literature, I argue that parties like the BJP can moderate in some ways while remaining radical in others. In short, electoral moderation can be limited and selective. I trace the limited and selective moderation of the BJP in the late 1990s and early 2000s to key changes in India’s party system including the decline of the historically dominant Congress Party, the rise of regional and caste-based parties, and the increased fragmentation of the party system that necessitated electoral alliances to govern. While analyzing key changes to the broader political and institutional context in which the BJP competes, I demonstrate that parties have a significant amount of agency to maneuver, pivot, and reposition themselves in their new institutional environments. In the case of the BJP, this meant limited and selective moderation that expanded its appeal among intra-Hindu identities, without substantive changes to the party’s approach to other religious groups. The second half of the dissertation focuses on explaining the limited and selective moderation of the BJP. A comparative analysis of the 2004 and 2014 elections reveals that two sets of relationships can constrain and incentivize limited and selective electoral moderation. One set emanates from within the party organization itself in the form of intraparty dynamics between the party, its workers, and other organizations within the Hindu nationalist movement. Second, the party is also constrained by the strategic interaction with its primary electoral rival, the Congress Party, to control the election narrative. A qualitative content analysis demonstrates how the Congress Party had an incentive to remind the electorate of the party’s ethno-religious strategies of mobilization from the past, even when ethnic parties like the BJP attempt to present a more ‘moderate’ face. These dynamic relationships within the BJP itself as well as its relationship to other electoral competitors can influence the party’s electoral strategies.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".