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Record W171836838 · doi:10.1108/01425451211248569

Hearing voice and silence during stressful economic times

2012· article· en· W171836838 on OpenAlexaff
Francine Schlosser, Roxanne Zolin

Bibliographic record

VenueEmployee Relations · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsSilenceConstruct (python library)PsychologyOpenness to experienceProsocial behaviorSocial psychologyNoticeOriginalityPerceptionSupervisorPolitical scienceCreativity

Abstract

fetched live from OpenAlex

Purpose It is ironic that in stressful economic times, when new ideas and positive behaviors could be most valuable, employees may not speak up, leading to reduced employee participation, less organizational learning, less innovation and less receptiveness to change. The supervisor is the organization's first line of defense against a culture of silence and towards a culture of openness. The purpose of this paper is to ask what helps supervisors to hear prosocial voice and notice defensive silence. Design/methodology/approach The authors conducted a cross‐sectional field study of 142 supervisors. Findings The results indicate that prosocial voice is increased by supervisor tension and trust in employees, while defensive silence is increased by supervisor tension but reduced by unionization of employees and trust in employees. This indicates that, as hypothesized by others, voice and silence are orthogonal and not opposites of the same construct. Research limitations/implications The data are measured at one point in time, and further longitudinal study would be helpful to further understand the phenomena. Practical implications This research highlights the potential for supervisors in stressful situations to selectively hear voice and silence from employees. Social implications This research also has implications for supervisors who work in a unionized environment. Although seemingly counter‐intuitive, there is a value to employee unionization in terms of either reducing the level of actual defensive silence, or at least reducing supervisors’ perceptions of defensive silence. Originality/value The paper adds to our knowledge of prosocial voice and defensive silence by testing supervisors’ perceptions of these constructs during difficult times. It provides valuable empirical insights to a literature dominated by conceptual non‐empirical papers. Limited research on silence might reflect how difficult it is to study such an ambiguous and passive construct as silence (often simply viewed as a lack of speech). The paper contributes also to trust literature by identifying its role in increasing supervisor's perceptions of prosocial voice and reducing perceptions of defensive silence.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.015
GPT teacher head0.233
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2012
Admission routes1
Has abstractyes

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