Bibliographic record
Abstract
Der Zusammenhang zwischen sozialen Kognitionen und schwerer relativer Armut in einem Industrieland ist von der Forschung bisher kaum untersucht. In einem Experimental-Kontroll-Gruppen Design wurden 42 Wiener Wohnungslose Menschen mit einer nach Geschlecht und Alter parallelisierten Kontrollgruppe verglichen. Emotion Recognition, die Fähigkeit Gefühle bei anderen zu erkennen, wurde mittels einer Kurzversion des Geneva Emotion Recognition Test (GERT-S, Schlegel & Scherer, 2016) erhoben. Die Experimentalgruppe zeigte signifikante Ergebnisse. Auch nach Aufnahme von analytischem Denken (erhoben durch Items des Standardized Progressive Matrices Test; Kratzmeier & Horn, 1988), Alexithymia (erhoben mittels der Toronto Alexithymia Scale; Kupfer et al., 2001), Empathie (erhoben durch den Saarbrücker Persönlichkeitsfragebogen zur Messung von Empathie; Paulus, 2009) und demographischen Daten in das Modell blieb der Gruppeneffekt auf den GERT-S Score signifikant. Die Ergebnisse widersprechen der Theorie Kontexualismus und Solipsismus (engl. contextualism and solipsism; Kraus, Piff & Keltner, 2011), die in Ermangelung anderer Ressourcen erhöhte soziale Fertigkeiten bei Menschen mit niedrigem sozioökonomischen Status annimmt.
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".