Bibliographic record
Abstract
Many fields in social sciences, such as criminology (Dubois & Vrancken, 2014), sociology (Rose, 1999), and social work (Rogowski, 2012), have spoken out against the dangers of psychologization, that is, the tendency to pay exclusive attention to the subjective dimension of various phenomena, at the detriment of social components. Many social events and phenomena are indicative of the increasing importance of psychology in the public sphere such as the proliferation of reality shows focused on particular psychological issues (Hoarding; Buried Alive; Intervention) or the media coverage of spousal homicides, which focuses almost solely on the perpetrator's mental distress, thus omitting the sociopolitical aspects indicating that the great majority of these homicides are committed by men toward women (Ryan, Anastario, & DaCunha, 2006). The ubiquity of psychology in contemporary societies has become somewhat of a “social fact.” As we will demonstrate, social work cannot—and should not—resist this new psychologically informed social setting, but must critically engage with this manner of constructing social problems.
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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 | 0.016 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.093 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.015 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".