How a Brazilian Public University Understands Sustainability: A Study Based on Sociological Discourse Analysis
Bibliographic record
Abstract
This paper aims to analyze the sustainability discourse manifested by a public institution dedicated to higher education located in the northeastern region of Brazil, the Federal University of Paraiba, during the time interval between the years 2009 and 2020. It used Sociological Discourse Analysis as a research method. It also used the documentation produced by the institution as a data source, in particular its Institutional Development Plans and Management Reports, as well as the media content produced and broadcast by its television channel and magazine. The research also used conversations held with employees linked to organizational management and observations recorded through photographs. Some questions were the basis for the data analysis: Who is the speaker; What is the position of the speaker; Which audiences did the speaker target; What did the speaker silence in the discourse; How did the speaker organize the speech; The research discovered discursive positions, narrative configurations, and semantic spaces that revealed an institution focused on its social function. It used teaching, research, and extension activities to be active in contact with society but placed its internal challenges in the background. It emerged that, despite understanding the importance of sustainability, internal actions to transform the organization into a laboratory for experimentation in this sense decreased due to the prioritization of combating recurrent socio-economic problems.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".