Managing organizational memory with intergenerational knowledge transfer
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 to provide the systematic analysis of an innovative, intergenerational knowledge transfer strategy in a knowledge‐intensive organization. Design/methodology/approach The case study method was adopted to study the intergenerational knowledge transfer activities. A triangulated approach was employed in respect of the data collection, which included non‐participatory observation, focus groups, documentary analysis, and semi‐structured interviews. A pattern analysis of data account was undertaken. Findings Two models for intergenerational knowledge transfer are presented: the source‐recipient model and the model of mutual exchange. This research also shows how a context conducive to knowledge transfer was developed, and concludes that this context allowed both explicit and tacit knowledge to be transferred. Research limitations/implications Often ignored or underestimated this study highlights the need for motivation, inspiration, and empowerment in knowledge transfer. The main limitation of this study is the generalizability of the findings. Practical implications The two models for intergenerational knowledge transfer provide a rubric against which both old and new intergenerational knowledge transfer initiatives can be assessed to determine whether they are capable of encouraging the transfer of both explicit and tacit knowledge. Originality/value There is little empirical work on the design and implementation of strategies for managing organizational memory. The integrated models and empirical results of this study can serve as guides in that process.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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