Critical sensemaking: challenges and promises
Bibliographic record
Abstract
Purpose The purpose of this paper is to analyze current literature on critical sensemaking (CSM) to assess its significance and potential for understanding the role of agency in management and organizational studies. Design/methodology/approach The analysis involves an examination of a selection of 51 applied studies that cite, draw on and contribute to CSM, to assess the challenges and potential of utilizing CSM. Findings The paper reveals the range of organizational issues that this work has been grappling with; the unique insights that CSM has revealed in the study of management and organizations; and some of the challenges and promises of CSM for studying agency in context. This sets up discussion of organizational issues and insights provided by CSM to reveal its potential in dealing with issues of agency in organizations. The sheer scope of CSM studies indicates that it has relevance for a range of management researchers, including those interested in behavior at work, theories of organization, leadership and crisis management, diversity management, emotion, ethics and justice, and many more. Research limitations/implications The main focus is restricted to providing a working knowledge of CSM rather than other approaches to agency. Practical implications The paper outlines the challenges and potential for applying the CSM theory. Social implications The paper reveals the range of problem-solving issues that CSM studies have been applied to. Originality/value This is the first major review of the challenges and potential of applying CSM; concluding with a discussion of its strengths and limitations and providing a summary of insights for future work.
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 | 0.154 | 0.175 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.013 | 0.102 |
| Scholarly communication | 0.033 | 0.050 |
| Open science | 0.006 | 0.016 |
| Research integrity | 0.007 | 0.010 |
| 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".