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Record W4396528902 · doi:10.1590/1984-0411.91508-t

“The world through our eyes and by our voices”: what children say about rights, discrimination and differences, gender, and poverty

2024· article· en· W4396528902 on OpenAlexaff
Catarina Tomás, Carolina Gonçalves

Bibliographic record

VenueEducar em Revista · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPovertySociologyPsychologyGender studiesPolitical scienceLaw

Abstract

fetched live from OpenAlex

ABSTRACT In the context of the project SMOOTH - Educational Common Spaces, Passing through enclosures and reversing Inequalities (Horizon 2020, European Commission) and the subproject RED - Rights, Equality, Difference - as well as an epistemological, theoretical, methodological and ethical position, that puts in dialogue the Sociology of Childhood and Education Sciences, a qualitative research was carried out with children attending the 2nd Cycle of Basic Education, in a public school in Lisbon, within the subject of Citizenship and Development. A central aim of the Project, which is presented in this paper, is to analyse, from an active listening of the children, their conceptions about rights, discriminations and differences, gender, and poverty, and their lived/attributed subjective meanings. Methodologically, through observation, semi-structured interviews and focus groups, their voices, and by their proposal, materialised in the publication of a podcast episode. Qualitative content analysis enables us to exercise an understanding of what children say about these themes, what they have prioritised, reflected upon, and ignored. Their views about the world must be understood from their biographies and contexts.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.027
GPT teacher head0.334
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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