MétaCan
Menu
Back to cohort

Socio Economic Change of Barasat: A Case Study Berunanpukuria

2015· dataset· en· W2269673471 on OpenAlex
Iosr Journals

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

VenueFigshare · 2015
Typedataset
Languageen
FieldSocial Sciences
TopicSocial and Economic Development in India
Canadian institutionsnot available
Fundersnot available
KeywordsGeographySocioeconomicsPopulationCensusQuarter (Canadian coin)Economic growthDistribution (mathematics)AgricultureAgricultural economicsSociologyArchaeologyDemographyEconomics

Abstract

fetched live from OpenAlex

Berunanpukuria is the largest mouza in the Icchapur Nilganj Gram Panchayet of Barasat-I Block in North 24 parganas in West Bengal. Berunanpukuria is situated on the middle of Barrackpur-Barasat highway in the vicinity of Barasat town. The village is large with an area of 152.92 sq.km. It has a population of 2162(according to 2001 census.) In the past(before 10 years) time the village was fully dependent on agriculture and fishery. But after the education institutions were set up the village become a developed village and in future it will become educational hub as well as an urban area. Here the study mainly focuses on the identification of socio-economic and cultural transformation of the village due to set up of education institution (W.B.S.U & Kingston Educational institute). When the Kingston Educational Institute (Technical engineering college) was set up in 2004 the transformation started and then after 2009 when the West Bengal State University was established a huge change is seen in transportation facilities, income level, change in land use, social amenities of study area, as well as density of population per sq-km, increase of total population, house construction, employment both male and female, health care facilities, increase of literacy, change of food habit, dress patterns, house amenities, nutrition distribution, bank account, etc.Therefore an attempt has been made here to identify the socio-economic and cultural transformation of the village and its benefit.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.277
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.2880.011

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 head0.229
GPT teacher head0.378
Teacher spread0.149 · 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