Outcome and process frames: Strategic renewal and capability reprioritization at the Federal Bureau of Investigation
Bibliographic record
Abstract
Abstract Research Summary Framing is critical for leaders who must build support for strategic renewal. While research has concentrated on renewal that replaces one set of capabilities with another, we explore a distinctive challenge: how leaders persuade stakeholders to endorse the reprioritization of resources toward a capability set that must coexist with an existing one. Moreover, while research has focused on how leaders build employee support for renewal, we examine how to persuade those overseeing resource allocation. Our study analyzes Director Robert Mueller's 12‐year effort at the FBI—after the 9/11 terrorist attacks—to build up counterterrorism capabilities while maintaining existing law enforcement capabilities. We offer a novel distinction between outcome frames and process frames and discuss how each frame, sequenced properly, is relevant to strategic renewal. Managerial Summary This study examines how leaders can build support for strategic renewal when an organization must develop new capabilities while maintaining existing ones. We analyze how FBI Director Robert Mueller, in the wake of 9/11, used strategic communication—or framing—to persuade members of Congress overseeing the FBI's budget to support the development of new counterterrorism capabilities alongside its traditional law enforcement mandate. We highlight two types of frames: outcome frames (focused on what the organization seeks to achieve) and process frames (emphasizing how the organization operates). Our findings reveal that sequencing these types of frames is essential. By using outcome frames to address immediate concerns and shifting to process frames to resolve longer‐term tensions, leaders can build stakeholder support for complex resource reprioritization efforts.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".