Bibliographic record
Abstract
The term 'big house' - an ambivalently derisive expression in Ireland - refers to a country mansion, not always so very big, but typically owned by a Protestant Anglo-Irish family presiding over a substantial agricultural acreage leased out to Catholic tenants who worked the land. As rural centres of political power and wealth in Ireland, most big houses occupied property confiscated from native Catholic families in the sixteenth and seventeenth centuries. Their presence in the landscape, unlike that of England's 'great houses', long asserted the political and economic ascendancy of a remote colonial power structure. Whereas by the nineteenth century the English country mansion could be incorporated into a triumphal concept of national heritage, for most of Ireland's population, Ascendancy houses signalled division, not community. In a colonial country, such division reflected not just the typical disparities of class and wealth between landlords and tenants, but also difference of political allegiance, ethnicity, religion and language. Thus in a speech advocating the 1800 Act of Union, Lord Clare notoriously described Irish landlords as 'hemmed in on every side by the old inhabitants of the island, brooding over their discontents in sullen indignation'.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".