Bibliographic record
Abstract
Motivated reasoning (MR) refers to the influence wishes, desires, and preferences have on individuals’ cognitive processes including assessing, constructing, and evaluating. Research on MR indicates that individuals have the tendency to accept favorable information and be dismissive or critical of threatening information. Such tendency influences the choice of newspapers and other media sources they consume and the content within these sources they read. MR is found to impact partisan affiliations and to lead to attitude polarization inequality, enhanced discrimination and injustice. Certain discussions linked to disabled people lend themselves to MR such as the origin of disablement (the body, the environment, or both) and whether the characteristic that makes one being classified as a disabled person is a deviation or a variation (see discussions around Deaf culture and neurodiversity). MR enables a polarization between the different views evident. Nearly all aspects and impacts of MR influence the living situation of disabled people. As such the purpose of our study was to investigate how the academic literature around MR engaged with disabled people. Using SCOPUS and the 70 databases of EBSCO ALL we found only two academic articles that directly covered MR in relation to disabled people. We use the issue of evidence generation in academic literature and newspapers as one example for discussing the impact of MR on disabled people. We suggest some actions that should be taken in relation to MR and disabled people.
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 | 0.000 |
| 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) | 0.002 | 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".