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Record W148803797

A history of football in Australia: a game of two halves

2014· book· en· W148803797 on OpenAlexaboutno aff
Roy Hay, Bill Murray

Bibliographic record

VenueDeakin Research Online (Deakin University) · 2014
Typebook
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsFootballCONTESTChampionshipLeaguePopularityCompetition (biology)Political scienceMedia studiesIdentity (music)ImmigrationHistoryAdvertisingSociologyLawArtBusiness
DOInot available

Abstract

fetched live from OpenAlex

The fascinating story of the fastest growing sport in Australia and the ties it has to our culture and identity. In coming years football will continue to excite sports fans throughout Australia. The Socceroos will contest the world's leading nations on the international stage. The Asian Football Confederation Cup of Nations will be held in Australia in 2015. The Matildas will defend their Asian championship crownin 2014 and aim to qualify for the World Cup in Canada in 2015. Men and women can also look forward to another trip to Brazil in 2016 for the football competition at the Olympic Games. The beautiful game has grown in popularity and participation since the creation of the A-League in 2005, success in the World Cup in Germany in 2006 and entry into the Asian Confederation in that year. Football has shown that it can bring the entire nation together in international competition. Football has a long and fascinating history in Australia stretching back to the mid-19th century. It is a rich history, closely related to one of the main themes in this country's development: immigration and the problems of integration of successive generations into a rapidly evolving national identity. This history tells the story of the game in a lively and provocative account. Roy Hay and Bill Murray are respected academics, historians and lovers of the game they have followed throughout their lives.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.933
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.208
GPT teacher head0.418
Teacher spread0.210 · 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
GenreOther

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
Published2014
Admission routes1
Has abstractyes

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