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Record W3161616808 · doi:10.1111/1748-8583.12354

Employees perceptions of non‐monetary recognition practice and turnover: Does recognition source alignment and contrast matter?

2021· article· en· W3161616808 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueHuman Resource Management Journal · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsHEC Montréal
FundersHEC Montréal
KeywordsContrast (vision)PerceptionPsychologyTurnoverSupervisorSocial psychologyEconomicsManagementArtificial intelligenceComputer scienceNeuroscience

Abstract

fetched live from OpenAlex

Abstract Nonmonetary recognition originates from various sources (distal and proximal) and research has yet to examine the interplay among them. Results of a 2‐year time‐lagged study ( N = 221), employing polynomial regression and response surface analysis, revealed that when distal organisational nonmonetary recognition is aligned with recognition from proximal sources, employees had lower turnover intentions and, indirectly, were less likely to quit 2 years later. For the most part, these relationships do not differ significantly based on the level at which alignment of distal and proximal recognition occurs. In terms of contrasts, when distal recognition exceeds the level of proximal recognition from the supervisor, turnover intentions are higher. For other proximal sources (co‐workers, physicians and patients), turnover intentions were higher irrespective of the type of contrast. This study adds to the strategic HRM literature by showing that contrasts between distal and proximal recognition undermine HR practice perception and employees' organisational attachment.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.238
Teacher spread0.224 · 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