Institutional work amidst the financial crisis: emerging positions of elite actors
Bibliographic record
Abstract
We draw on the institutional work literature to analyse the rhetoric in mainstream media spawned by the global financial crisis. We identify the emerging positions (status quo, neutral and change) of actors on major themes (policy, practices, recovery and regulation) related to the crisis and the rhetorical processes used (appeals to expert authority, finding someone to blame, use of scenarios, and avoidance of critical discussion) to communicate these positions. We find that academics lead the charge for change in policy, relying mostly on rhetorical processes that involve the use of past scenarios and blame, but also often avoid critical discussion through over-generalization. In contrast, banks focus on changes in practices, mostly using future scenarios, finding specific others to blame, and also appealing to expert authority. The US Federal Reserve takes the lead on maintaining the status quo on regulation-related issues, largely through using various scenarios and appeals to expert authority. We also find a large number of neutral positions and interpret this as tacit support for existing institutions. We conclude by charting out a broader research agenda for further investigation of the actors-institutions interplay, particularly within the context of the financial crisis.
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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 | 0.024 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.017 | 0.047 |
| Scholarly communication | 0.026 | 0.012 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".