MétaCan
Menu
Back to cohort
Record W4394017645 · doi:10.53555/sfs.v10i1.2275

Generation Z Talent Management In Organisations: An HR Perspective

2023· article· en· W4394017645 on OpenAlex
Vijay Kulkarni, Prof. Nikita Rai

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHuman Resource and Talent Management
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)Talent managementBusinessHuman resource managementKnowledge managementProcess managementMarketingComputer science

Abstract

fetched live from OpenAlex

There are numerous generations working together in every organisation, and Z is the newest generation to join it. Wong, K. (2020). According to numerous surveys and scholars, Generation Z is different in its attitudes as well as its work ethics, upbringing, and attitudes about entitlement and family. By reviewing the existing literature on talent management of Gen Z as employees, this paper aims to reveal the thematic research trends on the subject. This research's contribution will provide a deeper comprehension and greater awareness of how Gen Z relates to the workforce and the workplace. The findings of this study offer a framework for understanding the most important issues that organisations face when attempting to successfully hire the generation just entering the workforce Gen Z's specially their relationship to the workforce and the workplace and talent management, skillset management and its importance. The requirement to adapt not just for the newest generation but also for the talent management of the new generation which will lead to cohesion and cooperation between generations makes maintaining human resources management (HRM), as well as an efficient workflow and atmosphere in the workplace. The study will generate information that will support further research, help HRM better serve Gen Zers' demands, and add value to the business. As a result, the study's context is fully described, including Gen Z characteristics, what they expect from employers and jobs in general, as well as present HRM trends and organisational adaptation strategies.(Stern, P. J. (2002)) The idea that employees in companies that strongly emphasise talent management techniques are more involved in achieving high performance and are happier in their jobs is supported by a number of research and analyses in this sector. Additionally, these companies produce better financial returns. This research paper explores the challenges and opportunities of talent management among Generation Z employees within organizations, with a specific focus on the perspective of Human Resources (HR) professionals. As Generation Z emerges as a significant segment of the workforce, HR departments must adapt their strategies to attract, engage, develop, and retain this generation of employees effectively. This paper delves into the unique characteristics, expectations, and preferences of Generation Z, providing insights into how HR can tailor their practices to align with the needs and aspirations of this cohort.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.455

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.259
GPT teacher head0.304
Teacher spread0.046 · 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