The Attribution-Neutrality Audit: Diagnosing whether employee merit is recognised before it is rewarded — Instructor edition
Year: 2026
Type: other
Abstract: The Attribution-Neutrality Audit is a teaching module for Master's programmes in human resource management and organisation studies. This is the instructor edition, whose files are restricted; teaching staff may request access. Appraisal promises merit, but merit is not directly observable. Managers infer it from what they see, and that is shaped by structurally advantageous yet performance-irrelevant characteristics: visibility, status, proximity, tenure, scale. Attribution Neutrality is the degree to which merit is recognised independently of these; it precedes organisational justice, because organisations do not distribute merit, they distribute its recognition. The module turns that construct into an instrument: a six-step audit that maps the recognition sequence, scores six mechanisms of distortion and localises where advantage substitutes for merit. This edition adds, to everything in the student edition, worked audits of all three anchor cases, a model dossier worked end to end with a specimen marked assessment sheet, and a teaching note. Access is restricted because that material functions as an answer key. The open student edition is at https://doi.org/10.5281/zenodo.22024202. The module operationalises Nkurunziza, V. (2026), "Attribution neutrality in performance management: Generalising neutral quality attribution to human resource management," Human Resources Management and Services, 8(4), 6218 (https://doi.org/10.18282/hrms6218), which generalises Neutral Quality Attribution from "The maturation tree of inclusive shared value (MTISV), a diagnostic framework for industry application. Illustration in the Rwanda's coffee industry", Social Responsibility Journal (https://doi.org/10.1108/SRJ-11-2025-1162). The three anchor organisations are composites. This is an independent teaching resource authored in a personal capacity.
Author: Nkurunziza, Viateur
Institution: RISEBA University of Applied Sciences
Language: English
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7203977548