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Record W4417377843 · doi:10.1080/0305764x.2025.2603212

Pupils’ perceptions of power dynamics in Portuguese schools: do they feel their voices are heard?

2025· article· en· W4417377843 on OpenAlexfundno aff
María Assunção Flores, Orlanda Tavares, Eva Lopes Fernandes, Fernando Ilídio Ferreira, Diana Pereira

Bibliographic record

VenueCambridge Journal of Education · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Educational Policies and Reforms
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaUniversidade do MinhoInternational Council for Canadian Studies
KeywordsPerceptionPortugueseDynamics (music)Power (physics)Qualitative research

Abstract

fetched live from OpenAlex

This study explores how pupils aged 9 to 17 in Portuguese primary and secondary schools perceive power dynamics and participation in decision-making. Drawing on focus groups with 74 pupils across 13 state schools, it examines the extent to which pupils feel their voices are heard. Although formal structures such as student councils and class representatives exist, findings suggest these mechanisms are largely superficial, with authority remaining highly centralised. Barriers to meaningful participation include weak communication and leadership practices that prioritise control over dialogue. The evidence shows that pupil participation is mostly consultative and dependent on adult mediation, with organisational gatekeeping, rather than pupils’ willingness, acting as the main constraint. These patterns suggest that, despite five decades of democracy, Portuguese schools continue to mirror hierarchical traditions rooted in the authoritarian past, revealing how enduring institutional cultures still hinder the full realisation of democratic participation in everyday school life.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0040.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.010
GPT teacher head0.328
Teacher spread0.318 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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