Poder interprofissional em cuidados intensivos: reflexão filosófica a partir de perspectivas foucaultianas e críticas
Bibliographic record
Abstract
Objective: To discuss the power relations among health care professionals in acute care settings and its interference in the process of knowledge building.Methods: In this philosophical paper, we explored the influence of power relations on knowledge building using a Foucauldian and critical perspective of Gramsci and Freire related to nursing and health care practices.Results: There are four sources of organizational power (decision-making, discretion, control of resources, and control of knowledge/network) that act at different levels of healthcare organizations.Intensive care units are an important segment of healthcare setting, and the complexity involved in the daily activities of professionals in this sector can lead to difficult power relations in the process of knowledge building.For instance, when professionals external to the ICU team that hold specific knowledge need to be contacted to help in cases, such as during organ donation and transplantation process.In this situation it is necessary to deconstruct the competitive power in order to build the collaborative power.Conclusion: Using Freire's and Gramsci's perspectives we argued that lack of knowledge contributes to competitive power which can be overcome if involved individuals engage in the learning process towards
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 | 0.040 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.007 | 0.032 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 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".