Motivating Knowledge Sharing in Diverse Organizational Contexts: An Argument for Reopening the Intrinsic vs. Extrinsic Debate
Bibliographic record
Abstract
In an effort to assess the generalizability of factors that influence the disposition of knowledge sharing within organizations, this paper replicates a previous study that provided support for intrinsic motivators playing a dominant role in organizational science literature but applies it to a different community. A recent survey of 156 U.S. and Canadian law enforcement, forensic, and information assurance professionals discovered differences in the findings between the community examined in the earlier study and this one and suggest that there is merit in reopening the discussion between intrinsic and extrinsic motivators and the role they play in an organization. Examination of these two studies further suggests that the impact of motivators, both intrinsic and extrinsic, varies with the context of the knowledge management system to which they are applied. This paper then concludes with suggestions on direction of future research.
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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 | 0.065 | 0.120 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.006 | 0.033 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".