Agnostic Interactionism and Sensitizing Concepts in the 21st Century: Developing Shaffirian Theory-Work in Ethnographic Research
Bibliographic record
Abstract
In this paper, we reflect upon our experiences taking a graduate qualitative methodology course with Dr. William (Billy) Shaffir. We highlight Billy’s approach to ethnographic research and his declaration to “just do it.” Rather than just absorbing theoretical knowledge from the literature, Billy taught us to be wary of the dangers of a prior theorization and how it can distort rather than shed light on empirical investigations. Despite his belief that sociological theory is far too often abstract and removed from real-world contexts, he nevertheless provided us with a latent theoretical commitment to concept formation, modification, and testing in the field that guides our research to this day. We explore Shaffir’s agnostic and at times ironic approach to theory and demonstrate how his specific type of theory-work, derived from Everett Hughes’ and Howard Becker’s interactionist perspective on “people doing things together,” influenced how many of his students study occupations and organizations via sensitizing concepts. Billy managed to get us to think differently about how we theorize in the field and how to cultivate a playful and healthy skeptical attitude towards its application. This type of agnostic-interactionism does not dismiss theory outright, but is always vigilant and mindful of how easy it is for practitioners of theory to slip into obfuscation and reification. We conclude with a Shaffir inspired theory-work that argues for the continuing significance of an agnostic stance towards ethnographic and qualitative inquiry; one that continues to sensitize the researcher to generic social processes through which agency-structure is mediated and accomplished.
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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 | 0.114 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.006 |
| Science and technology studies | 0.017 | 0.182 |
| Scholarly communication | 0.022 | 0.030 |
| Open science | 0.004 | 0.020 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".