Broadening the Focus: Toward a Contextualized Understanding of Employee Voice and Silence
Bibliographic record
Abstract
Whether employees express (i.e., voice) or withhold (i.e., silence) their ideas, questions, opinions, and concerns at work affects individual and collective development and well-being. Employee voice is a precondition for employees to realize their potential, for organizations to deal with current management challenges (e.g., inclusion of forced and voluntary migration, diversification of life-style choices, dynamization of innovation), and it is essential for the functioning of current management strategies (e.g., total quality management, agile teams) that draw upon proactive and empowered workers. If, in turn, employees do not want to or feel that they cannot address critical issues or make suggestions for change, unhealthy, inefficient, unsafe, and toxic work environments endure and management gives away potential in the form of valuable contributions from diverse perspectives. Moreover, as media reports show time and again, such silence enables unethical practices including fraud, abuse, and discrimination to persist over time, harming cohorts of people repeatedly and at times over many years. Notably, cases of silence and their detrimental effects are not only observed in the corporate world or in singular countries, they also happen in sports teams, educational establishments, entertainment, academia, religious institutions, law enforcement agencies, and the military all over the world. Given that silence has been identified as hampering the sustainable development of organizations and societies in a broad variety of countries and contexts, surprisingly little systematic knowledge is available on the role of context as an antecedent of silence, and as a factor that influences the effects of more proximal antecedents of silence. In this symposium, five talks provide integrative and exploratory approaches to advance understanding of the role of context for the emergence and endurance of silence in organizations. In an extended discussion, Elizabeth Morrison – a central researcher on silence in organizations – will reflect on the journey the concepts of voice and silence have taken during the last 25 years and provide an idea of where the field might head to. The discussion will then open and we invite the presenters and audience to elaborate on challenges and opportunities that context provides to advance silence and voice research and intervention. Tystnadskultur – Using culture as a framework to examining collective silence Author: Michael Knoll; Leipzig U. Author: Lotta Dellve; U. of Gothenburg Predicting Silence through Behavioral Integrity Profiles Author: Jennifer Ho; DeGroote School of Business, McMaster U. Author: Catherine Connelly; McMaster U. The role of moral disengagement in explaining the link between workaholism and voice and silence Author: Roberta Fida; Aston Business School Author: Michael Knoll; Leipzig U. Author: Ivan Marzocchi; Sapienza U. of Rome Author: R H. Searle; Adam Smith Business School, U. of Glasgow Author: Catherine Connelly; McMaster U. Author: Matteo Ronchetti; Department of Occupational and Environmental Medicine, Epidemiology and Hygiene Social mobility concerns as a driver of employee silence in emergent markets: A study in India Author: Anindo Bhattacharjee; Woxsen U., Hyderabad, India Author: Michael Knoll; Leipzig U. Author: Wim Vandekerckhove; EDHEC Business School Silencing and voice in sexual harassment and abuse in medical training: A Case study Author: R H. Searle; Adam Smith Business School, U. of Glasgow Author: Lewis Garippa; U. of Dundee
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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 | 0.021 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.011 | 0.048 |
| Scholarly communication | 0.023 | 0.030 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.008 | 0.011 |
| 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".