カナダ・アルバータ州エドモントンにおける一般消費者に関連する情報システムの具体例とその背景の考察
Bibliographic record
Abstract
2007年9月から,6ヶ月の予定で,教員海外研修として,アルバータ大学エクステンション学部において現地の情報システム関連のフィールド調査を行っている.ここでは,アルバータ州エドモントン市における一般消費者に直接関係する情報システムの例として,銀行の預け払いシステムについての調査研究を行い,そこから,ヒューマンインタフェースを含む情報システムに対する一般消費者の考え方の一旦を明らかにした. In the period of my oversea study and research program or six months from September, 2007 I have been in Faculty of Extension University of Alberta. Here, I have studied and researched ICT(Information and Communication Technology) and venture businesses in ICT field. In this paper, as one of the result, I described the actual situation about information system of banks for personal consumers in Canada and the difference of recognitions of society between Japan and Canada which shapes the difference of service level in this field. I would like to express my special thanks to Faculty of Extension University of Alberta for their support.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.045 | 0.007 |
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".