Trobada: reinventar les trobades organitzades a través de la relacionalitat radical
Bibliographic record
Abstract
Els investigadors de ciències socials i sociològiques busquen cada cop més explorar el potencial de facilitar trobades organitzades entre grups socials conflictivs, amb l'esperança que aquestes reunions puguin promoure un canvi social positiu. Avui en dia, un gran conjunt de pràctiques es basa en aquestes interaccions orquestrades per intentar reduir el conflicte entre les diferències socials, religioses i culturals. No obstant això, argumentem que aquesta creixent literatura tendeix a assumir concepcions limitades de grups, punts de vista estrets del poder i idees lineals de temporalitat. Basant-nos en els desenvolupaments emergents en la teoria sociològica relacional, posem en primer pla l'ús del verb trobar-se (com un procés dinàmic de relació) en comptes de trobada (com un esdeveniment discret) com a marc alternatiu per als investigadors a mesura que faciliten, gestionen i interpreten aquestes reunions orquestrades. Avançar el relacionalisme radical d'aquesta manera, argumentem, aporta nova llum sobre la dinàmica multifacètica emergent d'aquestes reunions, cosa que permet una comprensió més complexa i profunda de com funcionen. Per tant, el relacionalisme radical, a través de la idea de trobar-se, proporciona un marc alternatiu per dur a terme investigacions sociològiques sobre el que es coneix com a trobades organitzades.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.035 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 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".