Is the medium the message? Exploring the intersection of social media and collective action in the San José Bike Party
Bibliographic record
Abstract
ABSTRACTThe San José Bike Party (SJBP) is a diverse collective of cyclists gathering for monthly group rides around the urban centre of San José, California. By leveraging social networking platforms, the SJBP announces a route and theme just prior to the ride each month. We argue that organizing, producing, and participating in these rides constitute a political act which can help to promote civic engagement and collective action. Further, we explored the way in which collective action can be fostered via social media. Through analysis of semi-structured individual interviews, focus-group interviews, moving methodologies and field observations derived from researcher participation in SJBP events, we articulate the complexities of contested and negotiated meanings of the use of technology, social media and activism assigned to the event by participants, yielding these themes: Critical Analysis of Social Media's Influence, Political Expressions in the SJBP and Prefigurative Politics in the SJBP.KEYWORDS: Collective actionsocial mediabicycle activismqualitative research Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 The COVID-19 pandemic has directly impacted many of our physical and social interactions and has severely disrupted our physical cultures. With that proviso, it is important to mention that this interactive and continuing research took place prior to the pandemic which struck the world over a year ago and led to governments shutting down many public events like the San José Bike Party (SJBP). While the SJBP (and other Bike Parties) have worked diligently over the past year to provide various experiences involving riders and bicycles, including solo scavenger hunts, 'endless' rides that encourage riders to join at any point and in any direction or a suggested route, and the first ride back was the Orange Mask Ride, announced on (5/16/2021) a return to the format of rides that are reflected here in the data, narratives and experiences of those, including ourselves, who took part in these Bike Parties pre COVID-19.Additional informationNotes on contributorsJay JohnsonDr. Jay Johnson is a full professor in the Faculty of Kinesiology and Recreation Management at the University of Manitoba. His current multiple mixed qualitative methodological interdisciplinary research explores the impact(s) of climatic change on our physical experiences and the interfaces with the environment and climate change. He is investigating how Indigenous and non-Indigenous youth experience outdoor adventure/land-based education; community-based research examining the function of the bicycle, culture and community in activ(ism); bullying; sport doping; the use of marijuana and CBD by professional athletes; the Ultimate Fighting Championship (UFC) and the pandemic and health; and the cultural intersections of gender, masculinity, race, ethnicity, sexuality and homophobia in team hazing/initiation rituals. He has published extensively on hazing, co-editing Making the Team: Inside the World of Sport Initiations and Hazing with Dr. Margery Holman.Matthew MasucciDr. Matthew Masucci is Professor in the Department of Kinesiology and currently serves as the Associate Dean in the College of Health and Human Sciences at San José State University. His research is interdisciplinary and interrogates sport and physical activity through the lenses of cultural studies, philosophy, and critical sport studies. Current research projects include; a critical, historical, and political analysis of Mixed Martial Arts (MMA) and the Ultimate Fighting Championship (UFC), discourse surrounding the use of marijuana and CBD by professional athletes, and a multi-dimensional investigation of a local social movement called the San José Bike Party.Jessica ChinDr. Jessica Chin is professor in the Department of Kinesiology at San José State University. She is a physical cultural studies scholar whose interdisciplinary research centers on the ways socio-cultural, political, and historical contexts intersect with participation experiences and the construction of identity through sport and physical activity. She critically investigates questions of gender and racial ideology, power, and representation in physical culture, focusing in particular on the meanings and experiences of Bike Party movements, sport hazing and initiation rituals, sport in communist and post-communist settings, and Asian American sport participation.
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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 | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".