MétaCan
Menu
Back to cohort
Record W2319428357 · doi:10.1080/01490400.2015.1095660

Perceptions of Power Within a Membership-based Seniors' Community Center

2016· article· en· W2319428357 on OpenAlexaff
Karen Gallant, Susan Hutchinson

Bibliographic record

VenueLeisure Sciences · 2016
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPower (physics)Center (category theory)Citizen journalismCitizenshipPerceptionSociologyPublic relationsPsychologySocial psychologyPolitical sciencePoliticsLaw

Abstract

fetched live from OpenAlex

As opportunities for citizenship diminish in everyday life amid increasing consumption and privatization, there is a growing realization of the importance of participation and citizen power, particularly for older adults. Gaventa's (1980) Gaventa, J. (1980). Power and powerlessness: Quiescence and rebellion in an Appalachian Valley. Urbana, IL: University of Illinois Press. [Google Scholar] concepts of visible, invisible, and hidden power and Arnstein's ladder of citizen power (1969) framed this study, which used participatory methods, including creation and facilitation of a members' group at a small seniors' center, to address the question: What are the factors that undermine or cultivate citizen power at a small community center for seniors? The data were organized under three power-related themes: powerlessness, reluctance to claim power, and claiming power. Findings suggest that negative social constructions associated with aging act as instruments of invisible power. Further, community center membership, to be considered meaningful, should be imbued with visible power, so that seniors can be involved in decision making and leadership.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0080.005
Scholarly communication0.0050.002
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.104
GPT teacher head0.440
Teacher spread0.335 · 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 designQualitative
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

Citations6
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueLeisure SciencesSame topicCommunity Health and DevelopmentFrench-language works237,207