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Record W18975229 · doi:10.1080/13691050802380974

SOLID ACID CATALYTIC ALKYLATION: A MEANS FOR GASOLINE-AROMATICS REDUCTION

2002· article· en· W18975229 on OpenAlexaff
A. Badakhshan, Mohammad Kazemeini, Farhad Khorasheh, Saeed Sahebdelfar

Bibliographic record

Venue17th World Petroleum Congress · 2002
Typearticle
Languageen
FieldChemical Engineering
TopicCarbon dioxide utilization in catalysis
Canadian institutionsUniversity of Calgary
FundersEconomic and Social Research Council
KeywordsAlkylationGasolineChemistryCatalysisReduction (mathematics)Organic chemistryMathematics

Abstract

fetched live from OpenAlex

This paper reports on findings from qualitative research conducted in the UK that sought to explore the connections between sexual identities and self-destructive behaviours in young people. International evidence demonstrates that there are elevated rates of suicide and alcohol abuse amongst lesbian, gay, bisexual and transgender (LGBT) youth. Rarely included in this body of research are investigations into young LGBT people's views and experiences of self-destructive behaviours. Data from interviews and focus groups with young LGBT participants suggest a strong link between homophobia and self-destructive behaviours. Utilising a discourse analytic approach, we argue that homophobia works to punish at a deep individual level and requires young LGBT people to manage being positioned, because of their sexual desire or gendered ways of being, as abnormal, dirty and disgusting. At the centre of the complex and multiple ways in which young LGBT people negotiate homophobia are 'modalities of shame-avoidance' such as: the routinization and minimizing of homophobia; maintaining individual 'adult' responsibility; and constructing 'proud' identities. The paper argues that these strategies of shame-avoidance suggest young LGBT people manage homophobia individually, without expectation of support and, as such, may make them vulnerable to self-destructive behaviours.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.271
Teacher spread0.249 · 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 designSimulation or modeling
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
Published2002
Admission routes1
Has abstractyes

Explore more

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