Bibliographic record
Abstract
President's column Wealth is not new. Neither is charity. But the idea of using private wealth imaginatively, constructively, and systematically to attack the fundamental problems of mankind is new.—John Gardner Historical philanthropy was primarily driven by religious convictions or the desire to remain in power. Around the time of John D. Rockefeller, something remarkable occurred as the great wealth created by industrialization ushered in a different sort of giving, targeted at improving people’s lives. Rockefeller started as an office clerk at age 16, creating his own firm 4 years later. His success in building Standard Oil was unprecedented—the firm would eventually be broken up into more than 30 individual companies that would grow to become Exxon, Mobil, Amoco, Sohio, and others. He gave away most of his wealth, founding the University of Chicago and Rockefeller University, but much of the giving was targeted at achieving specific goals. One example was focusing on eradicating hookworm disease across the southern US. Oil industry leaders have a long tradition of philanthropy, just one more way our industry serves the public good. SPE has set aside a modest amount of money for disaster relief in areas where our members reside. To date, we have contributed more than USD 100,000 to various efforts including USD 10,000 each to relief efforts following this year’s 7.8 magnitude earthquake in Ecuador and the Fort McMurray wildfires in Alberta and Saskatchewan, Canada. Most of us donate to charities according both to our abilities to do so and our convictions. One of the things I have been most pleased to see is not the donation of money, but the time and energy SPE members have contributed to charitable causes. I joined SPE in 1975 and one of the first activities I participated in was a section activity to raise money for scholarships, one of the most common areas for giving. SPE members have often been ready to volunteer for many efforts designed to benefit the public or deserving individuals or groups. I am thrilled to see sections and chapters around the world contributing their time and efforts to a wide variety of activities. In June, the SPE Board of Directors adopted “SPE Cares” as the name for global SPE volunteer initiatives, thereby promoting community service worldwide while bringing together students and young and experienced professionals. We can shed a positive light in the oil and gas industry and make a difference in our community outside our careers.
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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".