Delivering high-quality feedback is a choice: A self-regulatory framework for understanding feedback provision in organizations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Effective performance management depends on managers providing their subordinates with high-quality, corrective feedback when performance falls below expectations. Yet, there is considerable variance in the feedback that managers provide, and the current literature provides only fragmented explanations for why many managers sometimes neglect such a crucial behavior. To address this gap, we apply self-regulatory theories to develop a model of feedback-giving that integrates insights from the performance management and motivation literatures. We argue that feedback-giving is a goal-driven behavior that exists within a complex hierarchy of competing and complementary managerial demands. This theoretical lens provides much-needed insights to clarify reasons that managers may fail to devote sufficient effort to providing feedback to their subordinates. We conclude by applying our model to provide practical recommendations to improve performance management systems and leadership development programs in businesses. • A conceptual model of the motivational processes involved in feedback delivery is developed by drawing on self-regulatory theories of work motivation. • Providing feedback to subordinates is a behavioral means of pursuing a core managerial goal: maintaining subordinate performance. • Feedback provision is located in the middle of a managerial goal hierarchy, such that it facilitates pursuit of higher-order goals, and is pursued via lower order goals. • Feedback provision consists of several discrete behaviors, which can be characterized as being relevant to the feedback source, feedback content, and feedback delivery.
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.
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it