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Catherine Clémentin-Ojha, Le Trident sur le palais. Une cabale anti-vishnouite dans un royaume hindou à l’époque coloniale. Paris, Presses de l’École française d’Extrême-Orient (Édition-diffusion De Boccard), 1999, 365 p., annexes, gloss., index, ill. (« Monographies » 186)

2002· article· en· W39623864 on OpenAlexaboutno aff
Gérard Colas

Bibliographic record

VenueL Homme · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicSouth Asian Studies and Conflicts
Canadian institutionsnot available
Fundersnot available
KeywordsArtHumanities

Abstract

fetched live from OpenAlex

What drives our irresistible attraction to foods like chocolate, fries, or a warm apple pie? Sugar intake triggers the brain's dopamine system, creating a sense of reward that unconsciously conditions a preference for foods that satisfy cravings. Over time, this weakens attraction to healthier, low-fat and low-sugar foods. This response shares characteristics with addiction, sparking the concept of "food addiction." For early humans, this reward-driven behaviour was advantageous, motivating them to seek high-calorie foods essential for survival when food was scarce. Today, however, it fuels a global surge in obesity and diabetes the real "killer" of our times. Additionally, a study on fruit flies (Drosophila melanogaster) found that a sugar-heavy diet reduces sensitivity to sweetness, leading to increased consumption. This phenomenon, like "desensitisation" in humans, suggests that high sugar intake may promote obesity by altering taste perception and reward circuits [May et al., 2019]. The link between sugar-rich diets, obesity, and public health is a critical concern for healthcare professionals, policymakers, and the sustainability of the western healthcare system. A 2024 study published in BMJ [Lara-Castor et al., 2024] revealed that from 1990 to 2018, the consumption of sugar-sweetened beverages (SSBs) in children and adolescents (aged 3-19) from 185 countries rose by 23%, paralleling a global rise in obesity rates in this age group (Fig. 1). The findings highlighted a range of consumption levels influenced by factors like age, parental education, and urban living; however, the overall increase calls for national and targeted approaches to reduce SSB intake. Exactly like the prevalence of overweight (including obesity) among children and adolescents aged 5-19 has risen dramatically from just 8% in 1990 to 20% in 2022. While just 2% of children and adolescents aged 5-19 was obese in 1990 (31 million young people), by 2022, 8% of children and adolescents were living with obesity (160 million young people) [GBD 2019 Risk Factors Collaborators 2020; Okunogbe et al., 2022] (Fig. 2) [Ritchie and Roser, 2017]. Establishing good habits early is vital, as children are highly receptive to new behaviours. Notably, paediatric prevention begins even in the womb [Paglia 2017; Paglia, 2019]: a 2021 Canadian study [Laforest-Lapointeet al, 2021] linked maternal consumption of artificial sweeteners during pregnancy to an increased risk of infant obesity. By examining the gut microbiomes of 100 infants, researchers found that artificial sweetener intake could influence infant gut health and body mass index in the first year of life. The effects of sugar thus begin before birth and extend into early childhood. In Italy, added sugars are often introduced into infants' diets before 12 months, and delayed oral hygiene practices worsen the risks. Parental obesity further correlates with a higher incidence of Early Childhood Caries (ECC), emphasizing the need to address sugar consumption and health habits from prenatal to early childhood stages [D'oria, Bettocchi et al., 2024] Addressing the roots of obesity and diet-related diseases in young populations is therefore crucial and early intervention is key. In Italy, the government is attempting to curb sugar consumption through the so-called "sugar tax," introduced in the 2020 Budget Law. The tax was initially set to take effect on January 1st, 2021; but was postponed to January 1st, 2022. Then to January 1st, 2023; again to January 1st, 2024, and recently postponed once more to January 1st, 2025…Hoping next year will finally be the one!

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science 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 score0.525
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.226
Teacher spread0.213 · 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
Published2002
Admission routes1
Has abstractyes

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