“Surfing Alone”: The Relationships among Internet Communities, Public Opinion, Anomie, and Civic Participation
Bibliographic record
Abstract
Robert Putnam noted in his seminal essay “Bowling Alone” (1995) that the rich associational life that characterized Americans was being lost. He introduced the idea of “social capital”, or the formal and informal relationships among individuals, as correlates of social trust and civic engagement in a society. Robert Putnam neglected to note a more critical threat to social capital and traditional associations than “bowling alone”, however—the relatively new phenomenon of “surfing alone”, whereby individuals link to each other through the Internet. While this has often been hailed as a means of creating communities across spatial boundaries, it limits the face-to-face contact that has been critical to the political power of traditional organizations. As such, it provides an illusion of community that is a weaker counter-force to a dominant class. Further, as an international phenomenon, it has the potential to affect the levels of social capital on a global basis. This paper attempts to study the effects of “surfing alone” within the “internet community”, using data from the Saguaro Seminar at the John F. Kennedy School of Government at Harvard University. This project utilizes forty-one community-based samples from the study, for a total of 26,230 respondents in the United States. My paper concludes that the internet has a profound effect upon public opinion and civic associational life. To the extent that online contact replaces other forms of civic association, it promotes a public that is more isolated, less tolerant, and more susceptible to anomie than the traditional relationships.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".