Putting the pieces together: endometriosis blogs, cognitive authority, and collaborative information behavior
Bibliographic record
Abstract
OBJECTIVE: A discourse analysis was conducted of peer-written blogs about the chronic illness endometriosis to understand how bloggers present information sources and make cases for and against the authority of those sources. METHODS: Eleven blogs that were authored by endometriosis patients and focused exclusively or primarily on the authors' experiences with endometriosis were selected. After selecting segments in which the bloggers invoked forms of knowledge and sources of evidence, the text was discursively analyzed to reveal how bloggers establish and dispute the authority of the sources they invoke. RESULTS: When discussing and refuting authority, the bloggers invoked many sources of evidence, including experiential, peer-provided, biomedical, and intuitive ones. Additionally, they made and disputed claims of cognitive authority via two interpretive repertoires: a concern about the role and interests of the pharmaceutical industry and an understanding of endometriosis as extremely idiosyncratic. Affective authority of information sources was also identified, which presented as social context, situational similarity, or aesthetic or spiritual factors. CONCLUSIONS: Endometriosis patients may find informational value in blogs, especially for affective support and epistemic experience. Traditional notions of authority might need to be revised for the online environment. Guidelines for evaluating the authority of consumer health information, informed by established readers' advisory practices, are suggested.
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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 | 0.009 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".