Standing on the Shoulders of Goffman: Advancing a Relational Research Agenda on Stigma
Bibliographic record
Abstract
Drawing from Goffman’s original observations on stigma and the consequences of interactions between the stigmatized and supportive or stigmatizing audiences, we conduct a 20-year review of the diverse literature on stigma to revisit the collective nature of stigmatization processes. We find that studies on stigma’s origins, responses, processes, and outcomes have diverged from Goffman’s relational view of stigma as they have overlooked important relational mechanisms explaining the processes of (de)stigmatization. We draw from those conclusions to justify the need to study stigma as a collective phenomenon. We develop a relational perspective on stigma based on understanding how attributes are stigmatized (or not) by audiences in their interactions. We argue that to advance stigma research, it is necessary to build on Goffman’s theory to include the stigmatizers (i.e., the normal) and supporters (i.e., the wise); how they create, sustain, or remove stigma; and how they relate to the stigmatized (i.e., the targets). Accordingly, we provide a research agenda on stigma as a collective phenomenon that theorizes a relational perspective, proposes a typology of how audiences relate to stigmatization, and identifies patterns of relations between audiences. We thus offer a missing piece to existing accounts of stigma by focusing on the key role of audiences (i.e., stigmatizers or supporters of the stigmatized) rather than on the targets of stigma (i.e., the own).
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".