Characterization of the inter-individual difference in the response to social exclusion
Bibliographic record
Abstract
This project aims to update a shared dataset assessing the inter-individual variability in the response to social exclusion as caused by a Cyberball manipulation, and to provide related data analyses pipelines. Three self-report measurements assessing inter-individual variability are provided here: well-being (topp et al., 2015), loneliness (DiTommaso et al., 2007) and personality (lignier et al., 2023), based on previous insights from the ostracism literature (McDonald & Restrepo et al., 2024; Seidl et al., 2020). The dataset ("DATASET" excel sheet) comes with metadata ("METADATA" excel sheet). Feel free to reach bertrand.beffara@gmail.com for further details. References: DiTommaso, E., Turbide, J., Poulin, C., & Robinson, B. (2007). L’ÉCHELLE DE SOLITUDE SOCIALE ET ÉMOTIONNELLE (ÉSSÉ) : A FRENCH-CANADIAN ADAPTATION OF THE SOCIAL AND EMOTIONAL LONELINESS SCALE FOR ADULTS. Social Behavior and Personality: An International Journal, 35(3), 339‑350. https://doi.org/10.2224/sbp.2007.35.3.339 Lignier, B., Petot, J.-M., Canada, B., De Oliveira, P., Nicolas, M., Courtois, R., John, O. P., Plaisant, O., & Soto, C. (2023). Factor structure, psychometric properties, and validity of the Big Five Inventory-2 facets : Evidence from the French adaptation (BFI-2-Fr). Current Psychology, 42(30), 26099‑26114. https://doi.org/10.1007/s12144-022-03648-0 McDonald, M. M., & Brent Donnellan, M. (2012). Is ostracism a strong situation? The influence of personality in reactions to rejection. Journal of Research in Personality, 46(5), 614‑618. https://doi.org/10.1016/j.jrp.2012.05.008 Restrepo, A., Smith, K. E., Silver, E. M., & Norman, G. (2024). Ambiguity potentiates effects of loneliness on feelings of rejection. Cognition and Emotion, 1‑11. https://doi.org/10.1080/02699931.2024.2385006 Seidl, E., Padberg, F., Bauriedl-Schmidt, C., Albert, A., Daltrozzo, T., Hall, J., Renneberg, B., Seidl, O., & Jobst, A. (2020). Response to ostracism in patients with chronic depression, episodic depression and borderline personality disorder a study using Cyberball. Journal of Affective Disorders, 260, 254‑262. https://doi.org/10.1016/j.jad.2019.09.021 Topp, C. W., Østergaard, S. D., Søndergaard, S., & Bech, P. (2015). The WHO-5 Well-Being Index : A Systematic Review of the Literature. Psychotherapy and Psychosomatics, 84(3), 167‑176. https://doi.org/10.1159/000376585
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 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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".