Bibliographic record
Abstract
A key motto for communicators is 'Keep It Simple, Stupid!' or KISS in short. Sometimes though, even information specialists cannot speak clearly, and they end up transmitting convoluted and confused messages. This is lazy, since it often takes a lot of hard work to make a complex subject understandable in simple terms. Tough, but not impossible.\n\nOne complex topic is measuring the impact information has on agriculture (or any other field). Take the article on marketing information services in this issue of Spore as an example. If it helps ten MISs in ten countries to become sustainable, and thus enables years of profitable growth in agricultural trade, how much is thanks to the article? Do we include the impact on farmers incomes, and what that means for their children s education? If so, how much? The people who invest in information, including donor agencies, would just love to know the answers and apply them to their publications, rural radio, uses of the Internet and training seminars.\n\nIt is an inexact science, as a meeting on information impact assessment in October 2001 in Bonn, Germany, showed. Organised by CTA and the International Institute for Communication and Development with a range of specialised partners, this technical consultation made considerable progress at helping this new profession adopt common standards and evaluation frameworks. They have a lot to do still, in part in making their work understandable to outsiders, and especially to the people who invest in or contribute to it. Get to it, people.\n\nElsewhere, the Drumbeat network, experts in clarity, exchanges experiences in impact assessment and other concerns of information professionals in development.\n\n\n\nDrumbeat the Communication Initiative\n\n5148 Polson Terrace, Victoria, British Columbia, Canada V8Y 2C4\n\nFax: +1 250 658 1728\n\nEmail: wfeek@comminit.com\n\nWebsite: www.comminit.com
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; 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".