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Record W1998661298 · doi:10.1177/0021886301373005

When Organizational Voice Systems Fail

2001· article· en· W1998661298 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Applied Behavioral Science · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsMcGill University
Fundersnot available
KeywordsOrganizational justiceInjusticeEmployee voicePerceptionPsychologyInteractional justicePublic relationsSocial psychologyEconomic JusticeBusinessOrganizational commitmentPolitical science

Abstract

fetched live from OpenAlex

Recently, organizations have been introducing greater types and numbers of systems for employees to voice their complaints. Yet academic and popular accounts indicate that some voice systems are causing what they are intended to prevent, exacerbating employees’ perceptions of unfairness and discontent. Analysis of interview data from an inductive study of employees’ experiences of workplace injustice provides strong evidence of the deaf-ear syndrome (organizational failures to respond to employees’ complaints) and frustration effects (the pattern of increased dissatisfaction when people voice). Informal systems, namely, open-door policies, were particularly susceptible to failure. Drawing on organizational justice theory and industrial relations research, these results are explained, and additional avenues for research and theory development are acknowledged. Implications for individuals and organizations also are discussed.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.376
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.032
GPT teacher head0.316
Teacher spread0.284 · 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