SPE Strong: Strengthening Our Core: Reinforcing Core Strengths, Delivering Membership Value
Bibliographic record
Abstract
President's column SPE has always been strong and provides great value. I am one of those people who believes we can always be better. That is why I plan to emphasize our core strengths and how we can continue to build on them and grow stronger with the industry we serve. Members who take advantage of what SPE offers will find that it enriches their careers, as it has mine. I originally joined SPE as a student at the University of Alberta. At that time, SPE was relatively new to Canada, and the student chapter had only recently been established. The Petroleum Society of Canada, which focused on the Canadian oil and gas industry and later merged with SPE, was the predominant association preference among my peers. To me, SPE brought a global perspective on our industry along with strong technical content and excellent conferences. If you had asked me then what value SPE held for me, my answer would have been simple—a chance to network and learn from technical papers. While my fellow students and I were excited to be a part of the SPE family, we had little concept of the depth and breadth of value the society would provide for our future professional development.• My involvement in SPE has proven to be essential at each pivotal point in my career. As a young engineer, I would gladly pay for my own SPE membership even though I was counting pennies. I considered the annual dues an investment in my career, which continued to pay off repeatedly. I took on many different roles within SPE during my 29 years as a member—embracing positions that would develop my technical knowledge and soft skills, such as leadership and communication. So many doors of opportunity have opened for me because I interacted with my fellow members and utilized what SPE had to offer. The time spent on those SPE activities has always been a wise investment. As your president, I want to expand the value an SPE membership brings to both members and to companies that support their employees’ involvement in SPE. Our society is strong, yet I believe there are opportunities for improvement in the following areas:•• Gain recognition as the technical and unbiased source of information about our industry Develop trust within our industry and with the public Expand the value of membership and attract new members Illustrate value of attending SPE events against competitor events Increase manuscript citations and engage those from outside our industry who want to publish with SPE
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.017 | 0.014 |
| Open science | 0.001 | 0.016 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.059 | 0.029 |
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".