Bibliographic record
Abstract
Abstract Purpose – The purpose of this paper is to focus on the change experience of a regional health centre that was merged in the late 1990s and shows how organizational talk becomes privileged in the change process, and how some talk becomes meaningful in the constitution of organizational identity. Design/methodology/approach – The paper analyzes the process through which some talk is privileged in the organizational change process. The deconstruction of language used throughout this analysis highlights the relationship between sites of power and the ability to affect sensemaking among organizational members. Using a post‐structuralist approach, the authors apply the analytic framework of critical sensemaking (CSM) and critical discourse analysis. Findings – Organizational talk is presented as the enactment of a sensemaking process and insights are offered into the process of how organizational identities are maintained, altered or constrained during change. The discursive effects of the language of change, including the belief that change is actually a discursive process about the mutual constitution of language and identity in a process of making sense of the discourse of change, are discussed. Research limitations/implications – The merging of critical discourse analysis with CSM provides an alternative means of understanding organizational change, including the socio‐psychological processes that occur within the privileging of the language of change. Practical implications – For organizational change practitioners, the paper provides insights into the importance of how organizational members make sense of the change language discourse, which can affect how they introduce future change processes. Originality/value – The paper provides a novel way of understanding the change process and furthers the empirical use of (critical) sensemaking as a method.
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 | 0.015 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.066 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".