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Record W230568761

Why Did I Stay So Long

2007· article· en· W230568761 on OpenAlexaboutno aff
Randy Vlasin

Bibliographic record

Venue˜The œAgricultural education magazine · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsReading (process)PsychologyQuarter (Canadian coin)Class (philosophy)Mathematics educationPedagogySociologyHistoryPolitical scienceLawArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Twenty-four years. Why did I stay so long? When I first started teaching, I thought I would teach for a few years then go into world of agribusiness. I told myself, I would not stay in classroom long enough to teach my own children. All three sons went through my program. So, why did I stay for nearly a quarter of a century? It's quite simple really, I loved what I did. I found joy in helping young people learn and develop as human beings. To understand why I taught, you need to understand a little about me. I spent my first two years of formal education in a one-room country house. I was only one in my class, however there were eight other kids in that one-room ranging from kindergarten to 8th grade. I was a poor reader, spent more time day dreaming than studying, and couldn't wait for lunch and recess. By end of first grade, my reading had not improved much. That year, district consolidated and I went to school in town. The class was mammoth in size - a total of twenty-four kids! Hey, when you were used to being only one in your class, this was a huge increase. The upside, there was special assistance available called Title I that helped me with my reading. In eighth grade, we took IQ tests. I found out later that I ranked 3rd lowest in my grade. Fortunately, my teachers never treated me like someone with a low IQ score. I was an A to B student in every subject but math. To this day I tend to be skeptical of standardized testing scores. I noticed early on there was a difference in teachers. After becoming a teacher, I often looked back to those teachers who made a difference in my life. There was Mrs. Carse, who took me under her wing when I first came to the big school and was terrified because I didn't know anyone. She helped to comfort me and give me confidence that first year. She also provided extra assistance with my reading. There was Mrs. Shafer, my fourth grade She taught Nebraska History by allowing us to build miniature Native American villages and paper mache buffalo. There was Mr. Humprhey in sixth grade, who selected one of my English papers as an example of creative writing. Even though my handwriting was poor, he focused on story I created. I still remember how good that made me feel. Mr. Loose, my high math teacher, effectively taught me to draw houses and floor plans. Mr. Fiedler, our band instructor, taught me what excellence looked like and why it was important. All of these teachers and many others were beacons of light on road to what would become my profession, even though it would be many years before I knew it. My first serious thought of a career was in my senior year of high and focused on farming. My dad was a farmer, most of my uncles were farmers and it seemed a natural choice. I enrolled in Production Agriculture at Nebraska College of Technical Agriculture in Curtis, Nebraska with idea of coming home to farm in two years. However, I ran into a few teachers at NCTA who exposed me to a new possibility. These instructors seemed to really enjoy their jobs as teachers and it showed in their classrooms. I started to hear a whisper in back of my mind - Be a teacher. In fact, my high guidance counselor had suggested this before I graduated high school. I thought she was nuts. Four years of college, are you kidding me? I am going to farm! Eventually, I listened to voice and enrolled in Agricultural Education at University of Nebraska. It was best decision I ever made. My first real teaching experience, like most instructors, was during student teaching. I was fortunate to be placed with an excellent supervising teacher named Dave Creger. Dave wasn't your typical agricultural instructor. He came into profession later in life after farming and several other agricultural-related careers. I think one of reasons Dave was such a great teacher stemmed from his life experiences before coming to classroom. …

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.076
Threshold uncertainty score0.256

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0090.003
Scholarly communication0.0090.007
Open science0.0020.006
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0760.053

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 head0.020
GPT teacher head0.337
Teacher spread0.317 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations0
Published2007
Admission routes1
Has abstractyes

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Same venue˜The œAgricultural education magazineSame topicEducation Systems and PolicyFrench-language works237,207