Bibliographic record
Abstract
In Shades of Globalization Ailie Cleghorn and Larry Prochner examine the complex impacts of globalization on early childhood education in India, South Africa and Canada.The project is ambitious: each of the selected settings of early childhood education is beset by layers of complex and distinctive colonial histories.These three settings resist a comparative analysis in the conventional sense.With a mixture of program analysis and ethnographic field work methods Cleghorn and Prochner begin to unravel the various historical, economic, cultural and socio-political contexts and connections that shape the understanding and delivery of early childhood education in each local setting.At first glance one might wonder why Cleghorn and Prochner compare the operation of early education in, some ways, incomparable settings: within an indigenous community in a -first world‖ settler colony; a South African community afflicted by an apartheid past and; a modernizing India seized by poverty and the drive to modernize in the wake of British colonization.However, early on in the first chapter of the book the motivation for choosing and comparing these sites becomes evident.In our global times educating Aboriginal children in Littlelake, Canada seems to hold great resonance with the education of children in Tswane, South Africa and Valabh Vidyanagar, India.Perhaps the very existence of early childhood education in spaces where they previously did not exist is symptomatic of hyper-modernizing globalization.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.500 | 0.446 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".