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Record W3154978355 · doi:10.1108/ict-02-2020-0022

A case for increasing exemplary followership in organizations

2021· article· en· W3154978355 on OpenAlexaff
Debra Finlayson

Bibliographic record

VenueIndustrial and Commercial Training · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsFollowershipProductivityKnowledge managementOriginalityHuman resourcesBusinessValue (mathematics)SustainabilityPublic relationsManagementSociologyPolitical scienceComputer scienceQualitative researchEconomics

Abstract

fetched live from OpenAlex

Purpose In today’s rapidly changing workforce environment, organizations seek ways to increase productivity to remain competitive. The central human capital strategy is to attract the best talent and increase individual and team productivity to reach its strategic goals. Human Resources (HR) Professionals are required to attract, retain, train and develop employees to exhibit critical citizenship behaviours. The purpose of this paper is to present organizational-based research on why exemplary followers are considered valuable, as well as contribute to the understanding and discourse of the important role “exemplary followers” have for organizations. Extant followership constructs will be linked to key HR processes to illustrate how organizations can select, develop and retain “exemplary followership” to safeguard organizational sustainability. Design/methodology/approach A brief overview of HR systems and processes to enhance exemplary followership in employees is presented for training and development purposes. A range of research and practitioner papers are reviewed with the aim of illustrating the importance of and the key constructs for exemplary followership and to suggest practical applications for its development within organizations’ HR processes. Findings By understanding the importance and implications of exemplary followership development, the author will suggest practical HR tools that may be adopted, whole or in part, thus improving organizational sustainability. Practical implications Providing ways for HR to increase exemplary followership through learning and growth might help to expand practical followership development programmes in organizations at all levels. Originality/value This paper has drawn on limited followership organizational performance research done in the USA and Ghana and overall research in this area. It has discussed the Followership Continuum Model as a prescriptive tool for organizations to use. All Followership research has simply provided foundational constructs to be used in the original work the author developed for increasing exemplary followership in organizations through HR processes. There is no research like this to the author’s knowledge.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.276
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.132
GPT teacher head0.283
Teacher spread0.151 · 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 teacher head, 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

Citations3
Published2021
Admission routes1
Has abstractyes

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