Linking the Knowledge Economy to Prosperity in Continuing Education: A Preliminary Analysis
Bibliographic record
Abstract
This paper integrates the results of a comprehensive literature search on the topic of the knowledge based economy with a preliminary analysis of responses about the knowledge based economy from a Canada-wide survey of members of the Canadian Association for University Continuing Education (CAUCE). A knowledge based economy survey was developed based on ideas from the literature, tested on 15 staff members at 2 universities, and mailed to more than 500 CAUCE members. Sixty responses were received for a response rate of 12%. The literature and the feedback from the survey indicate that the knowledge based economy is making its presence felt in university continuing education more and more. The only collective definition that emerged from the CAUCE survey supported that highlighted by the literature, but a consistent understanding did not always guarantee support for the perspective. The challenges of establishing an effective internal learning culture, meeting the demands of the global market, and keeping abreast of the ever changing needs of clients and employers were not clear cut. The results of subsequent analyses of CAUCE member responses will incorporate comments from the presentation at the CAUCE meeting. (Contains 91 references.) (SLD) Reproductions supplied by EDRS are the best that can be made from the original document. Linking the Knowledge Economy to Prosperity in Continuing Education: A Preliminary Analysis Research Paper for the 47th Annual Conference of the Canadian Association for University Continuing Education June, 2000 David Castle and Gillian M. Joseph The Office of Open Learning University of Guelph Guelph, ON Canada N1G 2W1 U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) This document has been reproduced as received from the person or organization originating it. Minor changes have been made to improve reproduction quality Points of view or opinions stated in this document do not necessarily represent official OERI position or policy. PERMISSION TO REPRODUCE AND DISSEMINATE THIS MATERIAL HAS BEEN GRANTED BY
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.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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; both teacher heads agree on what is shown here.
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".