Bibliographic record
Abstract
If your organisation wants to tap into the wealth and influence of the rich and powerful, you need to know as much about them as possible. Prospect research, already used by fund-raisers with considerable success in the USA to target key people, can make all the difference to the success or failure of your initial approach. Targeting the powerful: international prospect research is a highly practical guide to prospect research, written by a leading expert. It explains how to conduct in-depth research into a person, company or charitable foundation, and how to use the information to recommend a line of approach most likely to succeed. Contents:What is prospect research?; Setting up a prospect research department; Online, CD-ROM, the Internet or paper? Ethics, security and confidentiality; Day to day questions; Finding the prospects; Marketing your organisation to the prospect; People; Company information; Foundations and trusts; International comparisons; A report on a new country; General sources for a new country; Specific international resources; The United Kingdom; Western Europe and Scandinavia; Central and Eastern Europe; Asia-Pacific; The United States; Canada; The rest of the world; Addresses; Index.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.040 |
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".