Auditing the ‘Social’ Using Conventions, Declarations, and Goal Setting Documents: A Scoping Review
Bibliographic record
Abstract
The state of the ‘social’ that individuals, social groups and societies experience are a focus of international conventions, declarations and goal setting documents. Many indicators of the ‘social’ and measures of well-being that contain sets of indicators of the ‘social’ exist to ascertain the state of the ‘social’ of individuals, social groups, and societies. Marginalized groups are well known to have problems with the ‘social’ they experience. Equity, Diversity, and Inclusion (EDI) and similar phrases are used in policy discussions to deal with ‘social problems’ within research, education, and general workplace environments encountered by women, Indigenous peoples, visible/racialized minorities, disabled people, and LGBTQ2S+. The prevention of the worthening of the ‘social’ is one focus of science and technology governance and ethics discussions. Many health professions are also concerned about the ‘social’ such as the well-being of their clients and their roles as stated by many of their associations include being advocates and change agents. The objective of the study was to ascertain how the ‘social’ is engaged with in conjunction with the following international documents (“Convention on the Rights of Persons with Disabilities”, “Convention on the Rights of the Child”, “Convention on the Elimination of All Forms of Discrimination against Women”, “Declaration on the Rights of Indigenous Peoples”, “Universal Declaration of Human Rights”, “International Convention on the Elimination of All Forms of Racial Discrimination”, “UN Framework Convention on Climate Change”, “transforming our world: the 2030 agenda for sustainable development” and “UN flagship report on disability and development Realizing the Sustainable Development Goals by, for and with persons with disabilities”; from now on called “the documents”). A scoping review using the academic databases SCOPUS, Web of Science, databases accessible under Compendex, and the databases accessible under EBSCO-HOST, coupled with a manifest hit-count coding approach was uses to answer five research questions: (1) Which terms, phrases, and measures of the ‘social’ are present in the literature searched (2) Which of the social issues flagged in the Convention on the Rights of Persons with Disabilities (CRPD) are present in the academic abstracts mentioning the other eight documents? (3) Which EDI frameworks, phrases and social groups covered under EDI are present in the literature covered. (4) Which technologies, science and technology governance terms and ethics fields are present in the literature covered? (5) Which health professions are mentioned in the literature covered? The results reveal vast gaps and opportunities to engage with the ‘social’ in relation to “the documents” covered for all five questions.
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 | 0.151 | 0.318 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.053 | 0.049 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".