The role of Information Technology in the Personnel Department: HRM in the Knowledge economy
Bibliographic record
Abstract
With the increasing possibilities of providing services to employees through Internet and Intranet applications, Human Resource professionals just need to click once or twice and a specially designed HR website leads to the required information. Employees would no longer be held responsible for the operational and administrative HR activities. Electronic-Human Resource Management (e-HRM) is the engine for pushing down the costs of any company and making it profitable. Information technology has been identified as an impetus of HR’s transition to becoming a strategic business partner. In this study, we extend this work one step further and explore the role of information technology in shaping the competency requirements of HR professionals. Key words: e-HRM; Human Resource Information Systems Resume: Avec une possibilite croissante de fournir des services aux employes via les applications d'Internet et d'Intranet, les professionnels des ressources humaines suffisent de cliquer une ou deux fois et un site web specialement concu pour les RH peut les conduire a l'information requise. Les employes ne seront plus tenus responsables pour les activites operationnelles et administratives des RH. La gestion des ressources humaines electronique (GRH electronique) est le moteur pour reduire les couts de la compagnie et la rendre rentable. Les technologies de l'information ont ete identifiees comme un nouvel elan de la transition des ressources humaines a devenir un partenaire d'affaires strategique. Dans cette etude, nous etendons ce travail un peu plus loin et explorons le role des technologies informatiques dans l'elaboration des exigences relatives aux competences des professionnels des RH. Mots-cles: GRH electronique; systemes informatique des ressources humaines
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".