Narrative Storytelling as a Fan Conversion Tool in the Netflix Docuseries <i>Drive to Survive</i>
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 paper explores how narrative storytelling converts individuals into sport fans. Data were collected through content analysis of Netflix’s Formula 1: Drive to Survive . Rhetorical criticism was applied to narrative elements identified in this popular docuseries. The conceptual framework drew from existing theories to detail how narrative storytelling effectively engages audiences and facilitates information exchange to achieve sport fandom. Findings show that the main narrative elements used in Drive to Survive were the plot types of adventure, ascension/descension, rivalry, and sacrifice, as well as the character type of hero. These narrative elements fostered sport fan conversion by providing multiple opportunities for information exchange, emotional connection, and inter-fan relationships. Ultimately, this study provides insight into conversion-through-narrative, strengthening the theoretical link between narrative storytelling and sport fandom by examining how narrative elements function in a successful case of sport fan conversion.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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