INTERMEDIATE GOODS INPUTS\nAND THE UK CONTENT OF IRISH\nGOODS EXPORTS. ESRI SURVEY AND STATISTICAL REPORT SERIES, July 2018
Bibliographic record
Abstract
This research aims to provide empirical evidence on the import content of Irishowned\nfirms’ exports of manufactured goods and how these firms may be\nexposed to changes in the trading environment after Brexit. Although a number\nof papers have examined the effect of Brexit on goods exports from Ireland to the\nUK by applying WTO-level tariffs, none to date have examined the extent to\nwhich goods exports may also incorporate imported intermediates or examined\nhow the effects of Brexit could differ across firms. The focus on imports of\nintermediate products in this report comes from their contribution to the export\ncompetitiveness of Irish firms. The key policy motivation in undertaking this\nanalysis therefore is to examine whether, and to what extent, the export activity\nof Irish-owned firms could potentially be exposed to disruptions in the supply\nchain coming from a negative effect of Brexit on their inputs from the UK.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.036 | 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 teacher head, 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".