Branding Bhakti: Krishna Consciousness and the Makeover of a Movement, by Nicole Karapanagiotis
Bibliographic record
Abstract
In Branding Bhakti: Krishna Consciousness and the Makeover of a Movement, Nicole Karapanagiotis examines the International Society of Krishna Consciousness' (ISKCON) rebranding efforts, which aim to increase the presence of Westerners within the movement.Using qualitative methods -such as participant observation, multi-sited ethnography, interviews, and ethnographic research -Karapanagiotis offers an updated account of ISKCON, focusing on the period between 2014 and 2018.The author highlights the need for literature to consider newly branded ISKCON spaces, beyond the "traditional" ISKCON temples, and attempts to fill this gap by offering glimpses into ISKCON-affiliated centres and programs.Karapanagiotis' multisited ethnography covers Philadelphia's Mantra Lounge, New York's Bhakti Centre, and the Govardhan EcoVillage outside of Mumbai.Karapanagiotis shows that the high population of South Asian diasporic community members within ISKCON has led to "rebranding" efforts by non-South Asian members, who want to attract more Western participants.Supposedly, this plan aims to follow the mission of the Indian founder of ISKCON, A. C. Bhaktivedanta Swami Prabhupada.As the most recent major academic study on ISKCON, this book offers a thorough understanding of the organization while raising important questions regarding how transnational movements maintain their success and livelihood through various tactics, including competition, promotion, and -most importantly -rebranding.ISKCON, colloquially referred to as the Hare Krishna movement, is perhaps best known for their adherents wearing orange
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".