Stigma Beyond Levels: Advancing Research on Stigmatization
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Stigma has become an increasingly significant challenge for society. Recognition of this problem is indicated by the growing attention paid to it within the management literature, which has provided illuminating insights. However, stigma has primarily been examined at a single level of analysis: individual, occupational, organizational, or industry. Yet, cultural understandings of what is discreditable or taboo do not come from the individual, occupation, organization, or industry that is stigmatized; on the contrary, they come from particular sources that transcend levels. As such, we propose that current silos within the literature may not only be preventing engagement with insights from different levels of analysis but, importantly, be preventing us from truly understanding stigmatization as a social process. To address this issue, we review the stigma literature and then present a cross-level integrative framework of the sources, characteristics, and management strategies therein. Our framework provides a common language that integrates insights across these levels and enables a shift in attention from how actors respond to stigma to broader processes of stigmatization.
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.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it