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Record W7133058179

Who belongs to the "creamy layer"? Affirmative action in Canada and India

2008· dissertation· W7133058179 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTSpace · 2008
Typedissertation
Language
FieldSocial Sciences
TopicPolitical Developments and Conflicts
Canadian institutionsnot available
Fundersnot available
KeywordsAffirmative actionReservationSupreme courtCharterGovernment (linguistics)ConstitutionDisadvantagedHuman rightsRace (biology)
DOInot available

Abstract

fetched live from OpenAlex

Canada and India are both pluralistic democracies with diverse populations. Both countries have drafted constitutional provisions which enshrine equality rights and permit affirmative action. In India, various disadvantaged groups receive special protection from the Constitution of India, such as the Other Backward Classes (OBC). The Supreme Court of India has held that States and the Central government must identify the "creamy layer" within the OBC category so that reservations target members who are most in need. Otherwise, the OBC category is overinclusive. The creamy layer includes those who are socially and economically advanced and who no longer require the benefits of the reservation system. Race based affirmative action may be overinclusive in Canada. For this reason, I argue that the Supreme Court of Canada should explore the concept of creamy layer in any of its future decisions on s. 15(2) of the Canadian Charter of Rights and Freedoms.

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.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.670
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.030
GPT teacher head0.352
Teacher spread0.322 · 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