Electronic Interaction in the Workplace: Monitoring, Retrieving and Storing Employee Communications in the Internet Age
Bibliographic record
Abstract
LegalFocus on Property and General Liability Insurance Volume 5, No. 7/8 LEGAL EDITORS Tom Hanrahan, LL.B. Zarek, Taylor, Grossman, Hanrahan, Barristers Paul Iacono Q.C., LL.B. Iacono Brown, Barristers PUBLISHER/EXECUTIVE EDITOR Anton Hart MANAGING EDITOR Dianne Foster Kent EDITORIAL ADVISORY BOARD Randy Bundus, LL.B. Insurance Council of Canada Alan Gahtan, M.B.A., LL.B. Mann Gahtan Glenn Gibson, A.I.I.C., C.L.A., F.C.I.A.A., C.F.E., C.F.E.I. CEO,Crawford Canada R.J. Gray, LL.B. Assistant Dean, Osgoode Hall Law School Lloyd Hackett Risk and Insurance Management Society Inc. Paul Martin Vice President, The KRG Group James D. McAuley Vice-President, KPMG Investigation and Security Inc. Michael Nobrega, C.A. Managing Director, Borealis Funds Management Ed Nolan Vice President, Halifax Insurance Glen J.T. Piller Vice-President, Claims, CIBC General Insurance Company Limited Robert G. Ryan Vice-President, Lombard Canada David Stewart Director Property Tax and Insurance, Cambridge Leaseholds Limited Michael P.Taylor, LL.B. Zarek, Taylor, Grossman, Hanrahan, Barristers Lee Thistle, C.F.E., C.F.E.I., C.I.F.I. C.O.O, TSI Solutions Paul Walters President, Walters Consulting Steven H. Wise President, The KRG Group David Wilmot, F.I.I.C. Senior Vice President, Toa Re ASSOCIATE PUBLISHER Barbara Marshall ART DIRECTOR/PRODUCTION Yvonne Koo CURRENT CONTRIBUTORS Michael Burkhart, Morgan Lewis Mark S. Dichter, Morgan Lewis Stacy King, emergit.com FEATURE AND KEYCASE
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 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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.012 |
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".