Social media integration in electronic human resource management: Development of a social eHRM framework
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.
Bibliographic record
Abstract
Abstract Social media has dramatically changed how we communicate both in life and in business. Accordingly, I conducted a qualitative analysis of electronic Human Resource Management (eHRM) practices involving social media. The sample consists of 16 organizations varying in size (e.g., Fortune 500 vs. small enterprises), industry (e.g., product vs. service‐based) and sector (public vs. private). Based on the review, I developed a Social Participation Framework involving two dimensions—openness and stratification— that are reflective of variations in the user domains associated with a given application. The combination of these dimensions yielded four alternative models of social media eHRM implementations: open, internal, specialized, and segmented. These in turn tended to be associated with different types of eHRM goals. A best practice example of each model is provided, and opportunities for future research are identified. Copyright © 2016 ASAC. Published by John Wiley & Sons, Ltd.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it