Identity, language, and ethnic relations in the Bilingual Autonomous Communities of Spain<sup>1</sup>
Bibliographic record
Abstract
This study surveyed 2446 undergraduates from five Bilingual Autonomous Communities (BAC) of Spain. We propose that the creation of the BAC of Spain in 1978 allowed the development of differing prototypic identities ranging from Spanish only identity, Autonomous only identity, and various permutations of dual Spanish/Autonomous identities. Based on their linguistic and ethnic self‐identifications, the percentage of participants endorsing each prototypic identity was monitored along with their key sociopsychological correlates. Six prototypic identity profiles were obtained. Results indicate that individuals endorsing the Autonomous only (11%) and Spanish only (13%) identities were more likely to engage in problematic intergroup relations. Strong Dual identifiers (9%) are the most likely to act as cultural and linguistic brokers and to foster intergroup harmony. Pro‐Spanish (15%) and Moderate Dual (7%) identifiers are more likely to benefit from language learning in the Autonomous language and emerge as cultural brokers. Esta investigación sondeó 2446 estudiantes de pregrado de cinco Comunidades Autónomas Bilingües (CAB) de España. Proponemos que la creación de las CAB de España en 1978 permitió el desarrollo de diferentes identidades prototípicas que van desde identidades solamente españolas, identidades solamente autónomas hasta varias permutaciones de identidades dobles españolas/autónomas. Basado en sus auto‐identificaciones lingüística y étnica, se observó el porcentaje de participantes que corresponden a cada identidad prototípica y sus correlacionados socio‐psicológicos claves. Se obtuvieron seis perfiles de identidad prototípicos. Los resultados indican que los individuos que asumen una identidad solamente autónoma (11%) y solamente española (13%) tienen más probabilidades de entablar relaciones intergrupales problemáticas. Los que tienen más probabilidades de comportarse como conciliador cultural y lingüístico, y de fomentar armonía intergrupal son los que asumen una fuerte identidad doble (9%). Los que asumen una identidad pro‐española (15%) o una identidad doble moderada (7%) tienen más probabilidades de beneficiar del aprendizaje de la lengua autónoma y se revelaron como conciliador cultural.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".