Bibliographic record
Abstract
At the IUPAC General Assembly in the middle of August this year, the Council decided to form a new standing committee, the Committee on Ethics, Diversity, Equity, and Inclusion (CEDEI), with the mission to work for the ethical values stated in the Union's strategic plan.This is a significant move because it underlines that international statements and recommendations, outlining ethical guidelines and principles for scientists, are not enough to guarantee that the scientific community "[strives] for diversity and inclusiveness in all forms, [respects] each other and the Union, and [upholds] the highest standards of transparent, responsible and ethical behaviour"[1].In fact, there are clear indications that the number and nature of violations of the 1979 Vancouver Convention [2], the 2010 Singapore Statement on Research Integrity [3], the 2012 San Francisco Declaration on Research Assessment (DORA) [4], the 2013 Montreal Statement on Research Integrity in Cross-Boundary Research Collaborations [5], and the 2016 ICSU Advisory Note on Science Communication [6], some of the relevant documents to abide to, have increased in recent years.Unethical research practices and behaviour are nothing new.Publication of "results" based on outright fraud has been known for centuries and increasingly harmed the scientific enterprise in recent decades.But just as worrisome is the growing number of other dubious practises, which include plagiarism, gift authorships, unethical refereeing, improper evaluations, and use of defamatory and insulting language in science-related discussions and debates among scientists.The purpose with all these acts is the same: to improve the likelihood for success in competitions for prestigious positions or appointments, research funding, and all sorts of awards, honours, and prizes.Such activities do indeed contribute to undermine the credibility of science, and this calls for a broadbased action in the scientific community at large.International organizations like the United Nations Educational, Scientific, and Cultural Organization (UNESCO), International Council of Science (ICSU), which in 2018 became International Science Council (ISC) have worked with dedication to strengthen the research integrity globally and nourish science practices based on equity, diversity, and inclusion.However, many of the obstacles to achieve this are Leiv K. Sydnes <leiv.
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 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 | 0.099 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.035 | 0.060 |
| Scholarly communication | 0.029 | 0.017 |
| Open science | 0.004 | 0.038 |
| Research integrity | 0.027 | 0.051 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".