Bibliographic record
Abstract
A resurgence of nationalism in Europe risks undermining the European integration project. Social Psychology and International Relations (IR) literature have explored how identities are created and strengthened through a process called ‘othering’ in which groups define themselves in opposition to others. Several variables contributing to this resurgence of nationalism exist, but ‘othering’ as a means of strengthening group identity appears to be among the most salient factors. This paper draws on previous academic research and uses a historical case study to argue that ‘othering’ in times of trouble and insecurity is not a new phenomenon. My research has focused on the changing public opinion among American citizens of English, German, and Irish descent during World War I. The methodology for this research required surveying primary and secondary sources published during the period August 1914 – April 1917 in order to glean evidence of changing public opinion of specifically the English diaspora. Throughout this process, it became apparent that a resurfacing of cultural and civilizational identities among the diasporas were often the source of changing opinion. Moreover, attempts by Irish and German-Americans to discredit English civilization and the Entente cause during the war actually served to strengthen Anglo-American ties and identities. This case study illustrates how the process of ‘othering’ may be used to bolster a sense of group identity in times of insecurity. This is something that appears to be occurring in Europe and has begun a process of European disintegration.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.024 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".