Introduction to the Special Issue: The Day-to-Day Lives of Cultures and Communities
Bibliographic record
Abstract
In a sense, the study of everyday life epitomizes the challenges and opportunities of ethnography. The papers in this Special Issue show how the close examination of the day-to-day lives of people in idiosyncratic settings can shed light on universal questions, complicate the elegant narratives we tell ourselves about what we know, enrich our theories, and expand our sphere of empathy. Although the study of everyday life can be traced back at least as far back as the turn of the 20 th century, reaching its apogee after the middle of the century, especially in the writings of Erving Goffman and Harold Garfinkel, it remains as uncommon as its object is commonplace. That is because it is easy to overlook the importance of what is happening when ‘nothing’ is happening and difficult to uncover what is significant about ‘the dust of social activity’. We argue—and the papers that follow show—that the details of the day-to-day can not only be unexpectedly interesting in their specifics but also a source of general theoretical insights about communities, organizations, and teams: their continuity, change and contradictions. What the papers have in common (with each other and with Goffman’s work) is an attention to the work that people do every day to sustain their particular self-image in the face of ongoing, mundane challenges of various sorts to the ways they like to think of and present their world and their place within it. This work to maintain the edges of meaning hides in plain sight and occupies us constantly, whether we are part of a public organization, a religious organization, a profit-seeking organization, a profit-resisting organization, an organization-less organization, or we are students of organizations marking the unremarkable.
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.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".