Community Engagement in a Conflict Environment: Reflections on the work of the International Fund for Ireland 1986-2011
Bibliographic record
Abstract
The International Fund for Ireland, which was set up by the British and Irish Governments in 1986 under the Anglo-Irish Agreement of 1985, was funded by the United States of America, the European Union, Canada, Australia and New Zealand. The International Fund enjoys the support of 31 countries, which is truly remarkable. It is one of the most successful examples of the Irish Diaspora at work in a very tangible way; a point ably captured in the Fund’s 2002 Annual Report where Hon Russell Marshall from New Zealand notes “As a member of the Irish Diaspora, New Zealand was delighted to be invited to join the Fund, and to lend its weight to the search for a permanent peace between the communities of the North, which had given so much to New Zealand’s early history”. The Fund had come into existence as part of an Agreement which did not have whole-hearted support in either part of the island at that time. It also came in the wake of many false dawns. While this had the effect of making life difficult for the fledgling organisation it would, in my view, come to be one of the drivers of its success as it became clear that the International Fund for Ireland (IFI) was part of a much larger story and the beginning of something really significant for this island.
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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 | 0.062 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.068 | 0.073 |
| Scholarly communication | 0.044 | 0.024 |
| Open science | 0.007 | 0.051 |
| Research integrity | 0.022 | 0.042 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".