Bibliographic record
Abstract
Abramitzky, Ran 127 abundance, and budgetary behaviour 210 accidental security challenges 26, 27-8 accountability 145, 203, 224, 232-3 active labour market policies 11, 12, 15, 44, 121, 128, 147 activist industrial policy 118 adaptation (small states) 19, 121 agility in 73 cooperation and 20, 203 culture and 18 flexible 44 to global markets 9, 13 and national elites 203, 229-31, 232 need for 8 New Zealand 170-76 speed of adjustment 27, 44 see also market liberal model; social investment administrative competence 46, 52, 54 administrative resources 61, 62, 69 advocates, budget games 208, 209 aggression, size as protection against 5-6 Ahtisaari, Martti 29 Air New Zealand 174 Alaska 213-14 Alberta Heritage fund 214 Alesina, Alberto 8, 9, 17-18, 212 Alliance of Liberals and Democrats for Europe (ALDE) 98-9 alliance protection 34, 44, 225-6 Alliance of Small Island States 27-8 Anckar, Dag 91 Andersson, Jenny 116 'Anglo-liberal' view, social policy 120 arc of prosperity/insolvency 158 Arctic strategy (Norway) 35-6 arguing strategies 65, 67-9, 70 armed neutrality 7 Åslund, Anders 187 Association Agreement with Ukraine 80, 87 associative pluralism 139-40 'Atlantic' attitudes 34-5 attachés 62 Auckland 179 austerity 150 Australia 166, 167, 168, 169, 170 Austria 7, 14, 48, 60, 104 autonomy/self-determination in diplomatic approaches 83-5 elite orientations 191-2, 194-6, 199 financial, Quebec 132 Iceland 50, 51, 55
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.652 | 0.408 |
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".