WeberWeb: Creation of an OER on Sociological Theory in Collaboration with Undergraduate Students
Bibliographic record
Abstract
Open educational resources (OER) have the potential to provide a wide audience with open access to quality educational content.It is not only a matter of offering access without direct charge to the end user; but fundamentally, that such resources are distributed under open licenses that allow access, reuse, adaptation, and redistribution.In this paper we describe the development of the website "Marianne & Max Weber: a digital project" (hereafter WeberWeb), an OER created in collaboration with students of the bachelor's degree in sociology at the faculty of political and social sciences of the Autonomous University of the State of Mexico. 1 This resource was created with the aim of supporting the teaching and learning tasks of a classical sociological theory course.The main characteristic of social sciences courses whose contents are completely theoretical is that the pedagogical strategies are focused exclusively on the reading and analysis of texts, either those written by prominent figures or by authors who analyze or apply them in their research.The project described here aimed to link the teaching of sociological theory with the creation of a digital project to produce an OER in Spanish that compiled, in one place, the main theoretical proposals of the sociologist Max Weber, as well as those of Marianne Weber, sociologist, pioneer of feminist studies, who also served as editor and posthumous compiler of her husband's work.In addition to promoting the development of digital skills among students, the collaborative creation of OER can contribute to making visible the work of people whose scholarly contributions have received less recognition because of their gender, race, or geographic location.To combat this absence and promote the acquisition of digital skills among undergraduate social science students, the WeberWeb project was born. Open Educational Resources as Part of the Open MovementWhat have traditionally been known as educational materials-understood as the media and resources that promote the acquisition of concepts, skills, attitudes, and abilities in support of the teaching-learning processare now not only physical, but also digital.However, not all materials available in digital formats are open for use by teachers and students.In most cases, it is necessary to pay either to have access to the resources or to the platforms from which they are available.In contrast, those learning, teaching, and research materialsavailable in any format and digital medium-that are in the public domain or whose copyrights have been released under open licenses are considered OER.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".