Understanding “disengagement from knowledge sharing”: engagement theory versus adaptive cost theory
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
Purpose – The purpose of this paper is using competing hypotheses (a spillover hypothesis, based on Engagement Theory, and a provisioning hypothesis, based on Adaptive Cost Theory) to help explain why employees become disengaged from knowledge sharing. Design/methodology/approach – Employed knowledge workers completed an online questionnaire regarding their job characteristics, their general health and wellness, perceived organizational support, job engagement and disengagement from knowledge sharing. Findings – The findings provide empirical support for Adaptive Cost Theory and illustrate the relationship between Engagement Theory and the Disengagement from Knowledge Sharing. In particular, this research illustrates the importance of health and wellness for preventing disengagement from knowledge sharing. In addition, the findings introduce a new finding of tensions between job engagement and knowledge sharing, which supports knowledge workers’ complaints of “being too busy” to share. Research limitations/implications – This study uses cross-sectional methodology; however, the participants are employed and in the field. Given the theoretical arguments that disengagement from knowledge sharing should be either short term or transient, future research should follow-up with diary methods to capture this to confirm the study’s conclusions. Practical implications – The findings of this study provide some insight for practitioners on how to prevent disengagement from knowledge sharing. New predictors and an interesting tension between job engagement and knowledge sharing are identified. Originality/value – This study examines an alternative explanation for the lack of knowledge sharing in organizations, and uses competing theories to identify the reasons for the disengagement from knowledge sharing.
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 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 | 0.016 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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