Bibliographic record
Abstract
Abstract Weak ties are relationships between individuals marked by relatively low levels of intensity and emotional closeness. By contrast, strong ties are relationships that involve high levels of intensity and emotional closeness. The importance of weak ties to a variety of sociological phenomena has been most influentially articulated by Mark Granovetter in the most cited article in sociology, “The Strength of Weak Ties” (SWT). Granovetter argues that most people intuitively expect strong ties to generally be more important than weak ties, because those to whom we are closely tied are more motivated to help us, and are also more likely to be stronger sources of social influence and social support. However, basing his argument on principles of social psychology, Granovetter argues that weak ties are – paradoxically – more important for a variety of phenomena, from helping people obtain a job, to the diffusion of ideas and innovations, to facilitating collective action. This entry describes the key theoretical underpinnings of Granovetter's SWT argument, and its application to various topics including job searches, and collective action and social movements. Also discussed are contextual issues, conceptualization and measurement, virtual networks, and related problems and future research.
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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 | 0.002 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 0.007 |
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".