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Record W2017702542 · doi:10.1177/0950017014545266

Towards Critical Human Resource Management Education (CHRME): a sociological imagination approach

2015· article· en· W2017702542 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

VenueWork Employment and Society · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsAthabasca University
Fundersnot available
KeywordsReflexivitySociologyContext (archaeology)Human resource managementPower (physics)InequalitySociological imaginationEpistemologyEngineering ethicsSocial scienceManagementEconomics

Abstract

fetched live from OpenAlex

This article explores the professional standing of the discipline of human resource management (HRM) in business schools in the post-financial crisis period. Using the prism of the sociological imagination, it explains the learning to be gained from teaching HRM that is sensitive to context, power and inequality. The context of crisis provides ideal circumstances for critical reflexivity and for integrating wider societal issues into the HRM curriculum. It argues for Critical Human Resource Management Education or CHRME, which, if adopted, would be an antidote to prescriptive practitioner-oriented approaches. It proceeds to set out five principles for CHRME: using the ‘sociological imagination’ prism; emphasizing the social nature of the employment relationship; investigating paradox within HRM; designing learning outcomes that encourage students to appraise HRM outcomes critically; and reflexive critique. Crucially, CHRME offers a teaching strategy that does not neglect or marginalize the reality of structural power, inequality and employee work experiences.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.876
Threshold uncertainty score0.718

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 communication0.0000.000
Open science0.0000.000
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 head0.034
GPT teacher head0.277
Teacher spread0.243 · 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