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Record W6991107438

An examination of the deprivation amplification hypothesis: an application to GAA pitches in Ireland

2022· dissertation· en· W6991107438 on OpenAlexaboutno aff

Bibliographic record

VenueCork Open Research Archive (University College Cork, Ireland) · 2022
Typedissertation
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousGovernment (linguistics)IrishQuarter (Canadian coin)Ideal (ethics)Rural areaInequality
DOInot available

Abstract

fetched live from OpenAlex

Research Question – This study analyses the levels of accessibility to GAA pitches and aims to discern whether those who live in more deprived areas have worse levels of accessibility, in line with the deprivation amplification hypothesis proposed by Macintyre (2007). The Gaelic Athletic Association (GAA) has existed since 1884 and is the governing body for indigenous Irish sports such as hurling and Gaelic football. GAA pitches are quite well dispersed throughout the country, which makes them ideal to gauge the levels of accessibility. 
\nResults and Findings – The likelihood of a GAA pitch being located in an electoral division is not affected by deprivation. It is found that in the majority of cases those living in more deprived areas do not have worse levels of accessibility to a GAA pitch. Those living in more deprived areas have a shorter distance to travel to a GAA pitch in an urban electoral division, but a longer distance to travel to a GAA pitch in a rural electoral division.
\nImplications and Recommendations – The results of this study offer insights into the levels of accessibility for sport facilities in Ireland. These results can inform the strategic decision making of sporting bodies such as the GAA, as well as the Irish government and policymakers in regard to the allocation of sports funding and grants, as well as the location of new sporting facilities.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0030.000
Research integrity0.0000.001
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 head0.083
GPT teacher head0.362
Teacher spread0.279 · 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 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
Published2022
Admission routes1
Has abstractyes

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