Recycling Stories: Mantras, Communication, and Organizational Materialization
Bibliographic record
Abstract
Religious non-governmental organizations (RNGOs) are becoming powerful organizational actors, but how are these organizations enacted through the communicative practices of their members? To address this question, this article offers a conceptual framework for investigating how the terse retelling of an inspirational organizational story, encapsulated in a mantra, contributes to materializing a Buddhist NGO’s ethos and worldview. The value of this framework is subsequently demonstrated through an in-depth naturalistic case study of a mantra’s constitutive force in the enactment of a large international Buddhist NGO that is increasingly focused on environmental protection. By showing how a mantra acts as a textualization, substantiation, and invocation device in mass, social media, and face-to-face communication, this study makes important contributions to the literature on the intersection between religion and organization as well as the communicative constitution of organizations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".