A Second-Class Workforce: How Neoliberal Policies and Reforms Undermined the Educational Profession
Bibliographic record
Abstract
Years of professional neglect, scrutiny, and inequitable pay have forced educators across the country to fight forimproved policies and reforms. A public, in some circles, that views educators undeserving of their salaries due to theunpreparedness of the American youth to succeed in the economy and the continued societal problems emanating fromthe profession.Neoliberalism, as a school policy plan, was designed to retool and establish improved schooling opportunities,especially for children of color located in poor residential environments. Instead, what it created was a more divided,tiered school arrangement that expelled black-and-brown teachers from education while closing down the schools theyworked in primarily situated in urban America (Lipman, 1998; Watkins, 2011; Apple, 2018).The methodology for this research diagnosed and assessed key aspects of contemporary literature along with applyingan auto-ethnographic lens to evaluate school reform challenges. The critical race theoretical approach was adopted toindicate how neoliberalism affects new teachers entering the profession along with teachers and children of colorexisting within school structures.Despite the paper identifying the various milestones achieved in the newly constructed schools, it is also clear thatcharter-and-contract school designs pay teachers less for their work, reduces the employment attrition rate, andconsummates an over testing industry that regulates and controls how teachers instruct and are evaluated. Moretroubling, fewer people were interested in pursuing this profession as a career (Walker, 2019; Ravitch, 2016).To fix this challenge, educators are in the streets, the school board rooms, and on Capitol Hill to demand theirprofession receive the types of reforms necessary to sustain its existence. Such activism ensures education willcontinue to make great strides improving the lives of children, every day, while also working to sustain communities inneed of hope and progress.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".