Researching Sustainable Communication:Constructively Critiquing Human Resource Management Communication Practices
Bibliographic record
Abstract
Ditlevsen and Johansen (2024) introduce in this issue the theoretical concept of sustainable communication as a response to a general call for a responsibilization of communication itself.Sustainable communication refers to communication practices that benefit not only organizations but also people and society at large.Moreover, Ditlevsen and Johansen (2024) present and discuss an integrated framework for sustainable communication -a framework that is based on three distinct yet interrelated mindsets, i.e., the ethical, the reflexive, and the critical, to be used for addressing communication as a responsible organizational function.Based on this, it is the aim of this paper to put forward and discuss illustrative examples of human resource management (HRM) communication practices through the lenses of sustainable communication.Three studies on HRM communication practices with a focus on the discursive construction of the employee (Kastberg & Ditlevsen, 2010; 2022;2023) serve as the empirical basis.The re-reading and discussion of the three studies follow the methodological framework for doing critical research proposed by Alvesson and Deetz (2021).Following this framework, this paper offers 1) insights, i.e., the outcome of an interpretation and a hermeneutic understanding of the empirical data, 2) critique, i.e., a discussion of the presented insights to expose hidden, taken-for-granted assumptions within the field of HRM, and 3) a transformative redefinition, i.e. "the development of critical, socially relevant knowledge and practical understanding that enable change and provide skills for new ways of operating" (Alvesson & Deetz, 2021, p. 19).By re-reading and discussing the three studies, it is shown that superimposing the tenets of sustainable communication onto everyday instances of HRM communication can shed new light on known issues and point to much-needed ethical, reflexive, and critically oriented avenues of research.The paper funnels into a discussion of what the implications of the insights gained and the critique offered could be for practice, including specific suggestions for practicing sustainable communication within the field of HRM communication.These suggestions take the form of concrete transformative redefinitions.
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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 | 0.075 | 0.097 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.010 | 0.057 |
| Scholarly communication | 0.026 | 0.033 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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".