Covid-19, Brazil and Canada: a relational and compared analysis
Bibliographic record
Abstract
The widespread of the COVID-19 pandemic has brought significant impacts on human relations, generating ample repercussions characterized by certain patterns of national and international relations. Taking this theme as a reference this paper is aimed to analyze the patterns of socio-political interaction in relation to the securitization of the COVID-19 pandemic in Canada and Brazil through a constructivist approach. The methodological basis of this research is characterized by an exploratory and descriptive nature according to its ends and as well as quali-quantitative to its means which is instrumentalized by the use of a comparative method and a discursive historical-theoretical-deductive logic. The results of the research indicate that the dynamics of national and international relations have become permeated during the pandemic by Lockean (competitive), Hobbesian (conflictive) and Kantian (consensual) the patterns of interaction due to an asymmetrical field of power that turns out to be more complex. It is concluded based on the results presented in the text that the interactional dynamics reported by Canada and Brazil demonstrate the convergence towards a negative apprehension of the COVID-19 pandemic in the social structure despite the different historical trajectories constructed on a Kantian pattern of relative consensus related to the decision-making processes in Canada in comparison to the Hobbesian pattern of intranational and international conflicts materialized in Brazil.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".