Stigmatization Dialogue: Deconstruction and Content Analysis
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
The present study examines the use of clinical rhetoric and discourse within the professional online forum "Gambling Issues International." The aim of this research is two-fold: (a) to examine the discourse of clinicians and researchers in defining gambling pathology; and (b) to investigate how professionals perceive the potential problems of stigmatization for their clients. Both qualitative and quantitative methodologies are employed in analyzing the data. Computer-based content analysis of listserv members' records is used to examine professionals' discussion of client and societal responsibility for gambling addiction, the diagnostic categorization of individuals, and the consequences of stigmatization. Quantitative methodologies utilize an online survey that is distributed to listserv members. The survey assesses how the medical model influences the discourse of researchers and clinicians in the field of problem gambling. The results of this research will contribute to an improved understanding of how the medical model creates such discourse and its role as a factor contributing to the stigmatization of clients.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 it